“music has no borders”: an exploratory study of audience engagement with youtube music broadcasts during covid-19 lockdown, 2020.

\r\nTrisnasari Fraser*

  • Faculty of Fine Arts and Music, The University of Melbourne, Melbourne, VIC, Australia

This exploratory study engages with eight case studies of music performances broadcast online to investigate the role of music in facilitating social cohesion, intercultural understanding and community resilience during a time of social distancing and concomitant heightened racial tensions. Using an online ethnographic approach and thematic analysis of video comments, the nature of audience engagement with music performances broadcast via YouTube during COVID-19 lockdown of 2020 is explored through the lens of ritual engagement with media events and models of social capital. The eight case studies featured virtual choirs, orchestras and music collaborations of various genres, including classical, pop and fusion styles drawing from European, Asia Minor, South African, West African, North African, Arabic, South Asian, and East Asian cultural origins. Five overarching themes resulted from thematic analysis of video comments, including Interaction , Unity , Resilience , Identity , and Emotion . The paper contributes important theorisation that ritual engagement and social learning fosters intercultural understanding through engaging with music both cognitively and emotionally, which can in turn shape both individual and collective identity. Online platforms provide scope for both bonding and bridging opportunities. Community resilience is supported through the sharing of knowledge, sustaining music practice during social distancing, as well as emotional support shared among audience participants, with potential wellbeing outcomes.


COVID-19 is highly contagious and lethal, with a cumulative global infection rate of over 72,000,000 and more than 1,610,000 deaths from December 2019 to the time of writing in December 2020 ( Dong et al., 2020 ). The exponential rates of infection and mortality have necessitated lockdowns in many countries, with wide-ranging social, cultural, economic and political disruptions. A rise in racist commentary, discriminatory responses and policies are acknowledged to be a threat equivalent to transmission of the virus itself, disproportionately affecting marginalized groups ( Devakumar et al., 2020 ; Ng, 2020 ; Wen et al., 2020 ).

During COVID-19 lockdown UNESCO launched the ResiliArt movement, a series of online debates with artists and cultural workers from over sixty countries about the impact of the pandemic on cultural industries. Among recommendations emerging from this movement is the necessity to share knowledge gained during the pandemic to ensure cultural diversity is promoted and safeguarded as cultural consumption increasingly moves to digital platforms ( UNESCO, 2020a ). Among the objectives of UNESCO’s 2005 Convention on the Protection and Promotion of the Diversity of Cultural Expression is the development of cultural interaction in order to build bridges among people. UNESCO (2017) subsequently supplemented the Convention with guidelines on its implementation in the digital environment, acknowledging “the emergence of new players and new logics” (p. 2) of how content is shared in the digital sphere.

During lockdown, musicians around the world adapted their music via digital means to continue to share a diversity of cultural expression and counter information distortion about the virus ( UNESCO, 2020b ). The current paper uses an online ethnographic approach to investigate audience reception of music from a range of cultures shared on YouTube during the COVID-19 lockdown between April and October 2020. The research investigates whether online music engagement facilitated social cohesion, intercultural understanding and community resilience.

Theoretical Framework

Mass migration and widespread use of global communication technology has led to renewed research interest in how to balance growing cultural diversity and social cohesion ( Putnam, 2007 ; Abascal and Baldassarri, 2015 ; Healy et al., 2016 ). Diversity of cultural expression through music may play a role in facilitating intercultural dialog and social cohesion. This is particularly pertinent in the context of both global and local responses to transnational threats such as global pandemics. To understand the social and cultural functions of music in an online environment during a global crisis, the theoretical framework of this paper draws on an interdisciplinary literature review, including the social and cultural role of music, media events as social ritual, social capital, information diffusion, online communities, and social-ecological models of community resilience.

The Social Function of Music

Music is a form of expression that demonstrates cultural variation while sharing many features across cultures ( Mehr et al., 2019 ). It has been touted as holding a key to collective identity formation through its practice and consumption ( De Nora, 2000 ; Hesmondhalgh, 2013 ). Existing empirical work has led to theoretical propositions that music functions as a means of social cohesion through neurohormonal processes, communication, coordination of action, empathy, and social cognition ( Dunbar, 2012 ; Koelsch, 2013 ; Clayton et al., 2020 ). Across cultures, social bonding and expression of cultural identity have been found to be important functions of music listening ( Boer and Fischer, 2010 ). During times of loneliness or curtailed social interaction, music listening appears to engender social cognition, playing a role as a social surrogate ( Schäfer et al., 2020 ). Compared to other social surrogates such as TV programs and fiction, music listening has been found more likely to lead to reminiscence of important social relationships ( Schäfer and Eerola, 2020 ).

Music also plays a predominant role in Emile Durkheim’s idea of “collective effervescence,” where shared identity, the enhancement of collective efficacy, and emotional communion is understood to emerge from participation in large scale ritualized gatherings involving music and dance ( Páez et al., 2015 ). Group singing has been associated with positive emotional experience, feelings of connectedness and increased group efficacy and performance ( Dingle et al., 2013 ; Good and Russo, 2016 ; Slater et al., 2018 ). Audience participation in live music events are understood to have positive social wellbeing impacts and to facilitate social capital ( Packer and Ballantyne, 2011 ; van der Hoeven and Hitters, 2019 ).

Research into how the collective social function of music gatherings translate in the absence of face-to-face encounter in digital environments is in its infancy. There is empirical evidence that virtual choirs–where people record individual performances in their own time and space that are subsequently edited together to represent a synchronous ensemble–elicit a sense of social presence for participants ( Fancourt and Steptoe, 2019 ). However studies in this special edition suggest the virtual choir during COVID-19 lockdown was experienced by participants as a stopgap measure–not as good as a face-to-face experience, despite some positive outcomes ( Daffern et al., 2021 ; Draper and Dingle, 2021 ).

Ethnographic research has also explored collective engagement with digital media events through the lens of social ritual. Applying a Durkheimian perspective, Couldry (2003) defined social ritual as habitual and formalized actions involving “transcendent,” or unifying values–for example nationalism or religious beliefs. Research has considered shared experiences such as building identity through televised cultural music and dance performance, as well as mediated self-disclosure via the internet ( Couldry, 2003 ; Pink et al., 2016 ). In an online context, Couldry (2003) found the shift from traditional centralized media to a decentred online network resulted in a “multiplication of centers” (p. 191), and thus multiple networks.

Social Capital and Online Communities

Social capital offers a theoretical framework based on networks, while also allowing for a useful perspective on efforts to balance social integration and cultural diversity online. As a broad concept, social capital refers to the resources an individual or group has access to in their social world. Numerous scholars have contributed to development of the term including Pierre Bourdieu, Nan Lin, James Coleman and Robert Putnam. This paper will focus on Putnam’s approach, as it offers a theoretical framework based on the value of social networks and shared norms primarily at the collective level ( Putnam, 2000 ).

Putnam’s (2000) investigation of social capital in the United States popularized research into social cohesion. He was concerned about the decline in social trust in American neighborhoods, and doubtful that the fledgling internet could adequately replace face-to-face communication in building social capital. He defined social capital as the social connections between people–the networks and associated norms of reciprocity and trustworthiness. His investigation considered bonding capital which reinforces exclusive identities and homogenous groups and bridging capital which is inclusive and encompasses diverse groups. Clusters of strong connections that characterize bonding capital have been argued to be important for the reinforcement of norms, obligations and expectations ( Coleman, 1988 ). Conversely, “weak ties” that characterize bridging capital have been argued to be important for information diffusion, access to novel ideas and integration of broader communities ( Granovetter, 1973 , 1983 ; Burt, 2005 ).

The success of cultural expression in creating bridges among people is predicated on engagement between different groups. On the one hand, commentators such as Benkler (2006) and Castells (2015) have argued online networks may facilitate more diverse social connections. On the other hand, the phenomenon of “echo chambers” or “filter bubbles” suggests homophily , the tendency to prefer association with similar people, is further reinforced online ( Pariser, 2011 ).

The formation of online communities has been considered from the perspective of weak ties ( Chen, 2011 ), affiliation formed via hashtags and online discourse ( Zappavigna, 2012 ) and communities of shared interests ( Baym, 2007 ). Debate has ensued regarding the nature of online ties–including the values espoused by online communities and the utility of online connections. While hashtags and online discourse can signal and create affiliation online, they are not always used inclusively, with the formation of “anti-social” communities advocating racist sentiments ( Kreis, 2017 ; Murthy and Sharma, 2019 ; de Saint Laurent et al., 2020 ). While Chen (2011) argued that sense of community online is largely imagined, in her investigation of Swedish independent music fandom, Baym (2007) characterized online connections as an ecosystem or “networked collectivism” that provided opportunities for computer mediated sharing of cultural products in real time and asynchronously.

Social Influence, Contagion, Homophily and Empathy

Existing social connections influence how music is shared using computer mediated communication, but access to broader networks online may accelerate information diffusion. Social learning theory ( Bandura, 1971 ) has been used as a model to understand change in music consumption based on the social influence of others online ( Dewan and Ramaprasad, 2012 ; Dewan et al., 2017 ). While the influence of proximal peers tends to dominate, popularity information available in online blogs can expose people to music consumed outside their immediate social circle ( Dewan et al., 2017 ). It is difficult however to distinguish the role of social influence from homophily through self-selection, an observation made both in research of online music sharing ( Bapna and Umyarov, 2015 ) and emotional contagion among YouTube audiences ( Rosenbusch et al., 2019 ).

Rosenbusch et al. (2019) noted the video format of YouTube may be stronger in impact for emotional content compared to message-based platforms such as Facebook and Twitter. Bandura (1971) observed that televised forms of modeling are particularly effective modes for social learning. Thus, YouTube may be stronger in impact for social learning about different cultures than message based platforms, particularly through the emotional medium of music. Empirical research suggests social norms related to racial bias may be implicitly learned by audiences through non-verbal cues on television shows ( Weisbuch et al., 2009 ). There is support, employing the same research paradigm, that affiliation with a cultural group can be strengthened by listening to culturally relevant music, an effect mediated by trait empathy and engaging in culturally relevant mental imagery ( Vuoskoski et al., 2017 ). While this previous research holds promise for combining cultural music and visuals on YouTube for strengthening affiliation with other cultures, it does suggest that individuals high in trait empathy may be more susceptible to this effect. Those high in trait empathy have similarly been found to be more susceptible to the emotional contagion effect of music ( Vuoskoski and Eerola, 2012 ). Rosenbusch et al. (2019) analysis of YouTube comments provided evidence of both emotional contagion and homophily among YouTube audiences. Where emotional contagion refers to the direct triggering of similar emotions through interactions with others, the authors offered cognitive empathy–the capacity to understand another person’s perspective–as an alternative explanation for the data, highlighting the difficulty of distinguishing these processes, particularly in an online environment.

Community Resilience in Complex Systems

Berkes and Ross (2013) proposed a model of community resilience that integrates literature regarding social-ecological systems with literature from health psychology. The former defines resilience as the capacity for the system to continually adapt to absorb disturbance and retain function. The latter regards community resilience as the capacity of the social system to come together through the exchange of knowledge and resources to work toward a communal objective in response to adversity.

The online environment may be considered a complex social-ecological system. In an online environment, the spread of information can be difficult to manage, and although decentralization of information dissemination can be seen as a democratizing force, as discussed previously, it may not always be used for prosocial ends. Furthermore, the spread of music online has been observed to be unpredictable and inequitable, with “information cascades,” where people follow the music choices made by others, fueling the exponential rise in recognition of certain music ( Salganik et al., 2006 ). As COVID-19 demonstrates, not all contagions are positive and the homogenizing effect of information cascades represents a threat to cultural diversity of expression online.

As an emotive medium with shared and distinct cultural features, ritual engagement with music online holds promise as a way to facilitate meaningful intercultural dialog, create broader affiliations between groups and enhance collective efficacy. Community resilience is argued to be strengthened through drawing on diverse cultural identities ( Grossman, 2014 ). However, as the online environment demonstrates homogenizing and polarizing forces, conserving a diversity of cultural expression online poses a challenge. To this end, UNESCO (2017) proposed institutional intervention. Despite observation that creativity in digital environments can circumvent institutional influence, with creators themselves becoming direct influencers of cultural production ( Mishra and Henriksen, 2018 ), research into social movements online suggests traditional media, organizations and opinion leaders, still play an important role in communication flows and social connections via online networks ( Sajuira et al., 2015 ; Hilbert et al., 2017 ).

Integrating a Diverse Set of Theories

To establish a theoretical framework to consider the role of online music engagement in facilitating social cohesion, intercultural understanding and community resilience during a global pandemic, a diverse set of theories has been considered. The following analysis draws mainly from a Durkheimian perspective of social integration through ritual engagement and a consideration of bonding and bridging social capital to understand cooperation within and between groups. Further consideration is given to interaction between different micro, meso and macro level processes. These include the mechanisms by which music might engender shared identity, including emotional contagion and social cognition, but also factors that influence the connections between people including processes of homophily, social learning, and information diffusion, which online appears to have both individual and institutional influences. Online connections and information sharing have implications for community resilience, as does the potential for music engagement to increase group efficacy and contribute to social wellbeing.

Study Aim and Research Questions

Using an online ethnographic approach, the study explored how audiences engaged with music performances broadcast online via YouTube as a ritual during COVID-19 lockdown. The analysis addressed the following research questions:

• What were the ritual elements of audience engagement with music broadcasts related to the COVID-19 pandemic?

• What role did this online music ritual play in engendering shared identity, and what mechanisms (e.g., emotional contagion, social learning, homophily) were implicated?

• How did different cultural identities interact as part of online music engagement?

• What factors influenced dissemination of the videos?

• How is community resilience enacted through online music engagement?

Data Collection and Participants

Due to the burgeoning volume of online music performance that emerged during COVID-19, an online ethnographic approach was adopted to filter the content. This involved the first author watching and interacting with music-related YouTube videos posted on their social media feeds from April 1st to October 30th 2020, and selecting appropriate videos for further analysis. The aim was to capture the first author’s experience of interacting with this material from Australia, as a community engaged dance and music practitioner with strong online connections to others engaged in intercultural music and dance. Supporting this approach, ethics protocol approval was provided by the University of Melbourne Human Research Ethics Committee (Application ID#: 2057554.1).

YouTube audiences were regarded as participants and their comments posted in response to videos were considered data. To protect confidentiality and privacy, their data were deidentified. To avoid traceability via online search engines, specific details of music performances are omitted in publication, the cultural origins of the music referred to in general terms, and quotations are paraphrased, as per a fabrication approach to qualitative online research described by Burles and Bally (2018) .

Materials and Methods

A total of 10 videos were selected for analysis. These videos were chosen on the basis that: they contained footage of a musical performance featuring a fusion of cultural styles, or culturally diverse engagement; were filmed and uploaded during the COVID-19 pandemic; included content relating to the COVID-19 pandemic; and had video descriptions in English. This followed a purposive sampling approach, where the selection criteria were applied in order to identify case studies that best addressed the research questions. The 10 selected videos each related to one of eight case studies. Performance details and number of videos analyzed for each case study are presented in Table 1 .


Table 1. Videos selected for analysis as organized by case study.

Thematic analysis was used to code and organize data, providing a methodological flexibility suitable for an exploratory study ( Braun and Clarke, 2006 ). The research is underpinned by a pragmatic philosophy that considers knowledge to be influenced by social experiences, and simultaneously constructed and real ( Biesta, 2015 ). YouTube pages were imported as PDFs into NVivo 12 for Mac ( QSR International, 1999 ) using NCapture.

Using this approach made all text on the YouTube page available for direct coding, including the introductory text for each video (in which the artist or organization often offers some explanation or description of the performance), as well as viewer comments. Line by line coding was used to assign comments in English to themes related to the stated research questions and to identify emergent patterns, using the NVivo manual text coding function. Thematic similarities and differences between case studies were analyzed. Coding and interpretation was refined through a process of investigator triangulation, drawing on a mixture of expertise and backgrounds in social and community psychology, sociology and critical studies ( Archibald, 2015 ).

The Context of Each Case Study

Case study 1: two performances by large scale community choir.

Case study 1 featured a live choir, established pre-COVID, which adapted to the online format during the pandemic using the virtual choir approach. Located in the Southern Hemisphere, the virtual choir attracted over 1000 participants from around the world to sing Western pop songs in English. Two of their performances were included in the analysis. Guide videos, instructions, and editing were coordinated centrally, allowing singers to participate with no more than a personal device and internet access. Using general information provided in the introductory texts, from the first to the second video there was a growth of approximately 50% in participation and 120% in the number of nations represented.

Case Study 2: Two Remixes of a North African Instrumental Created in Lockdown

An improvisation with a traditional North African instrument to the rhythm of a household appliance was remixed on two occasions. The original performance, which was broadcast from North America is not included in the analysis as the YouTube comments function was disabled. However, it is noteworthy that the shared cultural origin of the musicians and the name of the musical style was signaled by hashtag and keyword search terms in the original performance and in the two remixes included in the analysis, both of which were broadcast from Western Europe. One YouTube video remix featured the original footage, edited together with the remix artist’s own video recordings playing four additional instruments in the same cultural style. The second YouTube video remix featured the remix artist’s DJ logo superimposed over the original footage. The music was remixed in a Trap music style (sub-genre of Hip Hop) with electronic beats and samples.

Case Study 3: South African Song and Dance to Broadcast Health Message

Case study 3 was a performance coordinated and broadcast by an international organization, featuring a well-known singer adapting a South African pop song to communicate a health message about COVID-19. The song was sung in English. YouTube information revealed that dancers were chosen to be featured in the video after submitting their own home-recorded video performances dancing to the song. There were a large number of submissions, with 28 nationalities represented. Like case study 1, participation required only a personal digital device and access to internet, which appeared key in facilitating community engagement.

Case Study 4: North American and East Asian Orchestra Collaboration

The fourth case study involved a collaborative performance, by a professional orchestra located in North America and a student orchestra located in East Asia, in a Western classical style. Introductory text in the North American orchestra’s YouTube broadcast revealed the performance was an effort to adapt an ongoing joint endeavor between the orchestras to meet COVID-19 restrictions by using the virtual orchestra approach. Eighty musicians participated, fifty from the North American orchestra and thirty from the East Asian orchestra.

Case Study 5: World Fusion Music Collaboration–Charity Raising Effort

Case study 5 comprised 11 musicians of 10 different nationalities spanning West Africa, North Africa, South America, North America, East Asia, South Asia, Western Europe and the Caribbean. The composer of the song broadcast the video via his YouTube channel. It was sung in multiple languages, with the English version of the lyrics provided in the introductory text, along with a link for donations to an international disaster response organization. Accompanying video footage featured the musicians performing, intercut with shots of the disaster response organization’s activities in various communities around the world.

Case Study 6: Asia Minor Informal Orchestra

This performance featured 54 musicians, coordinated by two organizations, one located in the Northern Hemisphere, the other in the Southern Hemisphere. The orchestra performed a cover of a song in a vernacular style of music drawing on influences from Eastern Europe and Asia Minor. The song was sung in an associated language with lyrics provided in English in the introductory text. The majority (51.8%) of participants identified with a nationality associated with the musical style performed. Eight other nationalities were represented by 26.8% of the participants. The remaining 21.4% of participants identified transnationally.

Case Study 7: West African/Arabic Trio

Case study 7 featured a trio of musicians. According to the introductory text, the music performed was an Islamic invocation in response to current events. It was composed in West Africa by the broadcasting musician on a traditional instrument. He invited two other musicians to participate who were of Arabic descent, living in Western Europe. One musician accompanied on another instrument, the other sang in Arabic. The videos were recorded in each musicians’ home and edited together by the accompanying instrumentalist. The music was a fusion of West African, Arabic, and European styles.

Case Study 8: West African/Western Classical Duo

Case study 8 was a duo performed by two well-known artists. They played a cover version of a West African song, sung in the dialect of the composer, accompanied by Western classical instrumentation. The introductory text by the broadcasting musician was written in French and English, sending love, blessings and encouraging social distancing. The singer was of West African background, living in Western Europe and the accompanying musician was of East Asian background living in North America.

To investigate social interaction and engagement within case studies, first a line-by-line coding of viewer comments from all 10 videos was undertaken to ascertain common acts, sentiments or interactions. This allowed identification of indicators of the ritualized aspects of music participation, as displayed in the context of online media engagement. Identification of these ritual markers sets the basis for a subsequent examination, undertaken through the lens of Durkheim’s notions of social ritual and collective effervescence, as well as models of social capital. Following the establishment of overarching themes, a case-by case analysis identified converging and diverging themes.

Languages Other Than English

Comments in languages other than English (LOTE), apparent for all cases, provided data about the cultural diversity of the audience. Despite the brevity of many of these comments, automated translation was not used, to avoid losing nuances in dialog identifiable only with specific cultural knowledge, an issue previously noted in intercultural research on YouTube comments ( Oh, 2018 ).

Explanation of Main Themes

Five overarching themes resulted from coding and analysis of the data. In order of prominence, they included Interaction , Unity , Resilience , Identity , and Emotion . The Interaction theme captured all distinct examples in which audience members were interacting with each other. This was an emergent theme that captured the unique affordances of online platforms to facilitate dialog between users. As further outlined in the analysis, this had implications for the exchange of knowledge regarding collaborative music practice, lockdown experiences and cultural knowledge. The Unity theme captured group responses and comments about shared experience and identity. The Resilience theme included comments about experiencing and responding to adversity during the pandemic. The Identity theme captured comments regarding cultural identity, and personal and collective identification with the music. The Emotion theme captured references to and expressions of emotion.

Overview of Subthemes

Subthemes were derived directly from the data, and organized into the five themes above (see Table 2 ). These subthemes sought to capture the social nuances in basic text-based interactions. For example, the most common response across all case studies was a simple, positive statement directed toward either the performance (such as “Wow,” “Amazing”) or toward the performers (such as “Bravo everyone”). Such positive statements were interpreted to represent a group response, and initially coded collectively as applause . To account for the unique affordances that promote interaction between commenters online, with the possibility that an individual audience member’s comment may be read by performers and expanded upon by other views, those positive comments that were directed toward the performers were subsequently coded as a subtheme known as shout outs , distinct from applause , in that the former denotes Interaction , while the latter represents a sense of Unity . Another common audience reaction was signaling where they were in the world. This is analogous to the use of hashtags in signaling affiliation, in this case based on national identity, and was coded in the subtheme where are we from? , under the theme Identity .


Table 2. Themes and subthemes of thematic analysis.

Interaction subthemes included conversations, requests for information, requests to participate or indications of having participated, and comments related to the sharing of information. Unity subthemes comprised references to experiencing the pandemic together, shared identity and the role of music in uniting people. Resilience subthemes captured those comments that referred to the soothing nature of music, adversity in relation to the pandemic, and hope and positive change. Identity subthemes included LOTE, comments related to music evoking memories, acknowledgments of culturally diverse representation in the performances, and references to culturally specific aspects of the music. Emotion subthemes distinguished different emotional responses captured through comments including sadness, joy, mixed emotions and references to feeling moved or experiencing embodied responses such as chills.

Analysis of converging and diverging themes is included below with a sunburst diagram provided for each case study (see Figures 1 – 8 ). The diagrams provide a snapshot of the strength of endorsement of themes for each case. Subthemes that comprise each theme (as described in Table 2 ) are depicted by the segments in the outer circle of the diagrams and are listed for each case study. As it is not possible to present all variations, the main areas of convergence and divergence are discussed as they apply to the research questions, the literature or emerging themes.


Figure 1. Sunburst diagram of thematic analysis for case study 1, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 2. Sunburst diagram of thematic analysis for case study 2, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 3. Sunburst diagram of thematic analysis for case study 3, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 4. Sunburst diagram of thematic analysis for case study 4, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 5. Sunburst diagram of thematic analysis for case study 5, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 6. Sunburst diagram of thematic analysis for case study 6, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 7. Sunburst diagram of thematic analysis for case study 7, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).


Figure 8. Sunburst diagram of thematic analysis for case study 8, indicating proportion of data for each theme (inner circle) and subtheme (outer circle).

Case study 1 featured the largest scale performances with community participation. Themes identified for case study 1 are depicted in Figure 1 . Emerging strongly was the capacity for the online platform to support bridging opportunities. Weak online ties appeared to facilitate information diffusion and exchanges of advice and emotional support.

Conversations occurred between audience members which appeared to facilitate future participation either with the virtual choir, or as the comment below indicates, the use of the same approach in their own communities. Requests for information about how the choir was directed appeared only for this case study. An example of such an exchange was:

“ Did you use a special app for this or did you record separately and send in? I direct a choir and want to know how to do it .”

“ They asked us to record ourselves. I used my iPad and sent in the video. The team compiled all the videos .”

Expressions of support for those voicing loneliness were common and can be summed up by the following exchange:

“ On my own since January but great to see so many people feel the way I do, which is comforting ”

“ Hang in there! I’m on my 16th day, we are all alone, together ”

Coded under the theme Interaction , as they represented active audience engagement, these exchanges also relate to the theme of Resilience and sharing lockdown experiences , a category under Resilience that was prominent for this case study. These comments were interpreted as representing community resilience through the exchange of knowledge and emotional support in the context of responding to adversity.

Information diffusion was observed via comments indicating the source and subsequent sharing of information. The movement of information through micro, meso and macro levels of the social ecology was revealed by these comments. While sharing the link represents a micro level exchange online, offline this sometimes bridged geographical divides, for example, “This was shared with me in India by friends in Canada.” It was apparent that participants had heard of the choir through traditional media. Traditional media could be considered a macro level, and YouTube could be considered a meso level or bridge, for example, “I saw this on <TV show> and came to YouTube to see it close up.” As the songs were cover versions, they were accompanied by endorsements by the original performers, for example, “The band acknowledged this cover by sharing it.”

Coded under the subtheme I had a great time were comments from participants including, “Such a joy and privilege to participate in this choir” and indications of having participated in it with others–“So happy to have been a part of this with my sister.”

Nostalgia was a strongly endorsed subtheme under Identity . In some cases the music evoked emotional personal memories, for example: “When I was a little girl I had this on a record. When my mom got sick in hospital for a month, I would play this record and cry.” Other comments expressed emotion in the context of the music conjuring the passage of time, for example, “I grew up with this band. Now seeing all the young people in this video fills me with so much emotion.” Such comments also point to the role of music in creating collective identity.

Comments in LOTE including Portuguese, Spanish, German, Japanese, Korean, and Chinese suggested engagement by a culturally diverse audience. The audience commented on the cultural diversity in choir participation, for example “People from so many countries coming together.” One comment expressed dissatisfaction about representation “Not enough African faces.” This contrast, along with a similar pattern in case study 3, suggested an overarching shared identity was important to audiences, but so too was cultural representation.

Unique to case study 1 was the mixture of emotional responses. Most prevalent were comments related to tears, followed by joy. Mixed emotions were specifically expressed. There was an indication of emotional contagion–“Reading “tears of joy” made me burst into tears of joy.” Although isolated, this comment is notable for its explicit demonstration of emotional transfer.

Case study 2 was unique in this analysis in that musical collaborations were created organically through shared identification with a cultural form–a vernacular style of music and associated cultural identity, signaled through hashtags and keyword search terms. Emerging themes for case study 2 are depicted in Figure 2 . Audience comments were commonly characterized by familiarity with the culture and musical style, and in one case prompted an exchange between audience and producer:

Audience member: “How did you manage to make that sound like a ribab?”

Producer: “Research and observation and also it’s part of my culture.”

Comments in LOTE were prevalent, similar to case studies 5, 6, 7, and 8. What distinguishes these case studies from case studies 1, 3, and 4 is that they included non-Western musical styles and lyrics sung in LOTE. LOTE were most evident for this case study, with comments predominantly in Arabic, but also French.

Notwithstanding the clustering of Arabic comments in this case study, the presence of comments in other languages highlights the capacity for the online platform to reach a diverse audience, despite the hashtags signaling cultural specificity.

Although the performances were created during lockdown, they did not share the quality of other case studies of being produced as an alternative to live performance. They appeared more representative of new digital forms of cultural participation and practice where audiences become producers through remixing cultural artifacts shared online.

There are many parallels to the themes and subthemes identified for this study and case study 1 (see Figure 3 ), both cases involving community participation. Expressions of general appreciation for the music were prominent. There were expressions of shared experience–“We are in this together,” and shared identity–“We are a global family.” Although isolated, a counterpoint to this solidarity emerged through a conversation between audience members, likening the performance to propaganda:

Commenter 1: “Pure propaganda”

Commenter 2: “I agree – people indoctrinated into complacency”

Commenter 3: “What propaganda? Please explain”

The exchange provided a contrast to the expressions of emotional support and acknowledgment of shared experience evident in case study 1.

Audience members expressed a sense of nostalgia and identification, for example, “A song from my childhood,” and comments referred to the original composer and cultural origins of the song. Similarly to case study 1, there were both positive and negative comments about the representation of cultural diversity in the video. For example, “I like that many different African countries are shown, while there is no clip from countries which would dominate Western news,” and conversely, “I don’t see Côte d’Ivoire there.”

Emotional responses to the video were all characterized by joy or suggesting a humorous engagement, for example “Very funny.” Comparable comments were evident in case study 1 and may have been related to the community participation, with some individual submissions emphasizing humor and play.

In this case study, like case studies 1 and 6, music was expressed as a way to “unite the world.” Figure 4 provides an overview of the themes. Appreciation directed toward the musicians was prominent in the comments. Sadness was conveyed at the loss of opportunities to experience live music. Referring to the venue the North American orchestra would usually perform in, one audience member commented:

“ It is beyond sad when I walk by the venue. We are all waiting for it to come alive again with performances and audiences. Until then, thank you for these virtual performances .”

There were only comments in English and the language of the East Asian orchestra, although comments in English indicated audience participation from English speaking countries other than North America.

The subthemes emerging from the coding of case study 5 were similar to case studies 1 and 3, despite the lack of community participation in this case (see Figure 5 ). However, footage of disaster response efforts within communities may account for these converging themes, as well as the participating musicians themselves appearing to represent a community of like-minded artists with a select fan base.

Indeed, this case study featured brief responses by the broadcasting musician to comments by the audience, highlighting the capacity for direct connection between musicians and their fans, which in this case revealed some exclusivity in the engagement. A comment by one of the performers, “So honored to take part in this noble cause” further highlighted the permeable boundary between performer and audience in online platforms.

Emotion was expressed, which together with case studies 1, 3 and 4, suggest a propensity for at least some audience members to experience emotional responses despite the mediated form of engagement with the music.

This case study was similar to case study 2, also featuring a culturally specific vernacular style of music. As discussed in case study 2, this might account for the prevalence of comments in LOTE, predominantly Greek and Turkish. However, like case study 5, connections appear to have been facilitated through informal association with an existing community of musicians rather than finding affiliation online via hashtags, which did not feature in the introductory texts for this case study. Themes identified for this case study are depicted in Figure 6 .

Cultural diversity in music participation was observable through the video and the nationalities identified in the introductory text, but this was not commented on by audience participants. However one comment, made by a participant of the orchestra, acknowledged the effort of the Southern Hemisphere organization in facilitating a bridge between musicians located in the Northern and Southern Hemispheres.

The notion that music unites , overlapping with the theme of Resilience was encapsulated by the comment, “Musicians coming together across our troubled world.” Also coded under Resilience were comments suggesting participation in the performance brought hope, with some comments by participating musicians praising the conductor, for example, “you have been a catalyst and an inspiration.”

This engagement as both audience and participant has been discussed previously as emerging in case studies 1 and 5. This case study is more similar in nature to case study 5 than case study 1 with regards to the blurred lines between audience and participation. Although the musicians appeared part of a community rather than a formal orchestra like case study 4, they were nonetheless proficient musicians, rather than amateurs sourced from the broader community. As such, comments that personally addressed other participants were characterized by a certain exclusivity observable in groups reinforced by bonding capital. Indeed participation in this performance would have been predicated on knowledge of the particular musical style and audience comments sometimes simply stated the name of the style in the comments, seemingly as a way to signal recognition.

This case study (see Figure 7 ) continues a theme emerging from case studies 5 and 6 of comments suggesting engagement by a select fan base, with the broadcasting musician addressed by name on several occasions. Comments directed to the broadcasting musician, such as “Your music is a great healer” were acknowledged by the musician with a “love” reaction.

As has been discussed in case studies 2, 5 and 6 and likewise for the final case study that follows, comments in LOTE were prevalent. The performance was identified as an Islamic invocation in its title and introductory texts and the performance took place in West Africa and Western Europe. This confluence appeared to attract a culturally diverse audience, with LOTE including Arabic, French, Portuguese, Malagasy, Spanish, and Nyanja. The cultural significance of the music was discussed in terms of the use of traditional instruments, and vocalization in an Arabic style, for example, “Such sensitive playing on the kora.” Like case studies 2, 5, and 6, such comments suggest engagement by audiences familiar and interested in the musical genre performed.

This case study shares many subthemes under the theme Interaction with case studies 1 and 5 (see Figure 8 ). Case study 1 featured community participation and case study 5 featured audience engagement suggestive of a select fan base. Interestingly case study 8 featured two very well-known artists where there were many comments expressing love for the artists, addressing them by name. However, for this case, unlike case study 5, there were no exchanges between musicians and fans.

Comments in LOTE, included Portuguese, French, Nyanja and Spanish, suggesting diverse cultural engagement. A conversation ensued, exchanging knowledge about the dialect in which the song was sung:

Commenter 1: “The language is <dialect >, am I right?”

Commenter 2: “The song originates from < place >. Here a language close to <dialect 1> is called <dialect 2>”

Commenter 3: “So is she singing in <dialect 2>?”

Similar to the data for case studies 1 and 3, such exchanges suggested representation and acknowledgment of difference was important to cultural identity.

While some comments suggested personal identification with the music, such as, “I learned this song when I was 7 years old in Senegal,” others indicated exposure to new cultural experiences, such as “I don’t understand a word, but it’s so soothing.” The latter example illustrated the way music, as a non-verbal medium, can overcome language barriers, with potential to facilitate intercultural understanding.

The research aimed to investigate whether online music engagement facilitated social cohesion, intercultural understanding and community resilience during COVID-19 lockdown. Specifically, the study sought to address: (a) how audiences engaged with online music broadcasts as ritual; (b) the role played by online music ritual in engendering shared identity and the mechanisms implicated; (c) the interaction between different cultural identities as part of online music engagement; (d) the factors influencing dissemination of the videos; and (e) the way in which community resilience was enacted through online music engagement. Given the idiographic nature of this research, the results above offer an account of the potential social outcomes experienced by particular online communities during their engagement with music during COVID-19 lockdown. Rather than producing broad inferences, this research offers insight into the potential for connection in online spaces at a time when online spaces where all that were available to many around the world.

Engagement With Online Music Broadcasts as Ritual

Five themes emerged from coding of the data including Interaction , Unity , Resilience , Identity , and Emotion . These themes are consistent with psychosocial effects observed of ritualized collective gatherings in offline settings where emotional communion has been observed to strengthen collective identity, identity fusion, enhancement of personal and collective efficacy and positive social beliefs ( Páez et al., 2015 ). However, contrary to offline settings, emotional communion did not appear to be prominent in this study. The phenomenon of emotional communion is associated with synchronized behavior and shared experience in vivo . For the asynchronous engagement observed in these case studies, Couldry’s (2003) interpretation of Durkheim’s ritual theory of social integration, with its emphasis on collective knowledge over collective feeling is instructive. Couldry defined collective knowledge as “the cognitive processes and categorizations (inevitably more dispersed across space and not requiring us to congregate in one place) on which our knowledge of the social world is based” (p.22).

The ritualized nature of audience engagement with music broadcast via YouTube during the COVID-19 pandemic was characterized by positive group responses directed at the performance or performers and signaling of location around the world. Other ritual actions such as the use of hashtags or specific styles of online discourse ( Zappavigna, 2012 ) were not pronounced in the case studies selected. Case study 2 was a notable exception, featuring the use of hashtags and keyword search terms to signal affiliation with a specific cultural group and musical style. Case study 2 also diverged from the other case studies in the way the performances did not seem to represent an alternative to live performance. Rather the remixing of cultural products shared online represented emerging digital forms of cultural participation which blur the boundaries between cultural consumer and producer. The apparent collective ownership of a cultural product calls to mind Baym’s (2007) idea of the “networked collectivism,” and more democratic and participatory models of cultural production online discussed by commentators including Benkler (2006) and Mishra and Henriksen (2018) . As engagement with cultural artifacts online is predicated on knowledge of a cultural form, it is conceivable that cognitive mechanisms would be predominant.

Engendering Shared Identity and Implicated Mechanisms

Expressions of unity were observed, with references to shared humanity and music’s specific role in uniting people. The shared experience of the pandemic, and appreciation for musical performances also represented collective responses.

As discussed, although these were not prominent, comments by some audience members suggested an emotional response to the broadcasts that may have served to engender a sense of shared identity. However, there is insufficient data in this analysis to draw conclusions about the role of emotion in strengthening collective identity, or to surmise whether empathy played a role, as suggested by previous literature ( Vuoskoski and Eerola, 2012 ; Vuoskoski et al., 2017 ; Rosenbusch et al., 2019 ).

Identification with the music through a sense of nostalgia emerged for half of the case studies. Reminiscence and nostalgia through music listening as a form of social surrogacy has been associated with social cognition and connectedness, through bringing back memories of significant people or events ( Schäfer and Eerola, 2020 ). In this analysis, the memories evoked for some people were personal in nature, for others they communicated a sense of being part of a collective. What is interesting in this analysis, particularly in the context of music listening as a social surrogate, is the affordance provided by the YouTube platform to share personal memories with other users, which likewise potentially creates a sense of connectedness.

Representations of cultural diversity through the videos were noted positively by audiences, with the potential to facilitate future intercultural interactions. The affordances created by online platforms for interactions between audience members facilitated exchange of knowledge about specific cultural musical forms, providing opportunity for social learning.

A degree of homophily was apparent in certain case studies supporting more exclusive engagement, particularly those presenting vernacular styles of music associated with a specific cultural group. Despite this relative exclusivity suggestive of bonding capital ( Coleman, 1988 ; Putnam, 2000 ), the range of languages represented in the comments for these case studies pointed to some cultural diversity in engagement, supporting Benkler’s (2006) assertion of the prevalence of bridging opportunities online.

Interaction Between Different Cultural Identities

Although language may have been a barrier to bridging between different cultural identities via dialog, music appeared to emerge as a non-verbal medium that facilitated diverse engagement, an observation made in offline intercultural music engagement ( Vougioukalou et al., 2019 ). Exchanges about specific cultural knowledge including the use of traditional instruments, styles of vocalization and use of specific dialects revealed interaction between different cultural identities.

Music, representation and acknowledgment of differences all emerged as being important to cultural identity. It has been observed in the literature that the importance of acknowledging diverse cultural identities has implications for research and policy development in the areas of social cohesion ( Abascal and Baldassarri, 2015 ), community resilience ( Grossman, 2014 ), and for the way music studies are conducted ( Jacoby et al., 2020 ). The representation in the videos of transnational identities and diasporic communities underlines the complexity of culture and intercultural understanding in the context of globalization and widespread use of information and communications technology.

Factors Influencing Dissemination of the Videos

A number of factors appeared to influence dissemination of videos including individual shares, endorsements by opinion leaders, traditional media and organizations, consistent with previous literature ( Sajuira et al., 2015 ; Hilbert et al., 2017 ). Micro, meso and macro level processes appeared to intersect as part of a dynamic system, where individual shares could bridge geographic location, and information diffusion through traditional media led to online engagement. The YouTube platform emerged as an important bridge connecting musicians and producers with a wider audience.

The capacity to engage in dialog through the comments function also served to blur the divide between performer and audience, creating affordances for a range of levels of interaction, including in the case of a large-scale community choir, the possibility to participate in future online performances. This has implications for community resilience, discussed further below, but also for further dissemination of the videos through individual shares by participants themselves.

How Community Resilience Was Enacted Through Online Music Engagement

Well-known and lesser-known musicians, formal and informal choirs, orchestras and music groups broadcast via YouTube, used music for a range of purposes including charity raising efforts, morale boosting, broadcasting health related messages, and engaging global community participation. The use of music for all of these purposes has implications for building community resilience during lockdown. Acknowledgment of the shared experience of adversity, positive collective responses and interaction between audience participants represented displays of community resilience.

Both Hesmondhalgh (2013) in his analysis of the role of music in fostering collective identity and Couldry (2003) in his analysis of media rituals, referred to John Durham Peters book Speaking into the air , which challenged the notion that face-to-face is the only legitimate form of communication. Indeed, in this study, the sharing of music videos and online dialog appeared to create opportunity for meaningful exchange. Weak online ties translated into emotional support and sharing of knowledge. The data pointed to a shared sense of identity through both experiencing the pandemic and feeling buoyed by the music, but also to the importance of specific cultural knowledge and representation.

Limitations and Future Directions

A limitation of the study was that the data is idiographic in nature due to the ethnographic approach. Having been drawn from videos shared with the first author, from others actively engaged in intercultural music and dance, it is possible that the degree of cultural diversity of engagement is a function of the social network through which the data was sourced, itself representing a form of homophily–a shared interest in music of diverse cultures. While audience comments were suggestive of the emergence of social connections, intercultural dialog and resilient responses, the observations are not broadly generalizable. The study nonetheless points to the possibilities for bridging, intercultural understanding and cohesion afforded by the online environment through music engagement.

As an exploratory study, although the unobtrusive mode of data collection facilitated observation of social processes in a naturalistic setting, it precluded deeper understanding of the experience and motivations of participants. Future research that integrates alternate forms of data collection is necessary to better support extrapolation of findings.

Data Availability Statement

The datasets presented in this article are not readily available because the data are not publicly available due to them containing information that could compromise research participant privacy. Requests to access the datasets should be directed to TF, [email protected] .

Ethics Statement

The studies involving human participants were reviewed and approved by University of Melbourne Human Research Ethics Committee. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Author Contributions

TF conceived and designed the study, carried out the literature review, collected and analyzed the data, and wrote the manuscript. AC and JWD provided critical feedback on the data analysis. All authors contributed to manuscript revisions, approved the final version of the manuscript and agreed to be accountable for the content herein.

This research was supported by Australian Research Council Discovery Project (# DP190102978).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abascal, M., and Baldassarri, D. (2015). Love Thy Neighbor? Ethnoracial Diversity and Trust Reexamined. Am. J. Sociol. 121, 722–782. doi: 10.1086/683144

PubMed Abstract | CrossRef Full Text | Google Scholar

Archibald, M. (2015). Investigator Triangulation: A Collaborative Strategy With Potential for Mixed Methods Research. J. Mixed Methods Res. 10, 228–250. doi: 10.1177/1558689815570092

CrossRef Full Text | Google Scholar

Bandura, A. (1971). Social Learning Theory. New York: General Learning Press.

Google Scholar

Bapna, R., and Umyarov, A. (2015). Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks. Manag. Sci. 61, 1902–1920.

Baym, N. (2007). The new shape of online community: The example of Swedish independent music fandom. First Monday 12:8.

Benkler, Y. (2006). The Wealth of Networks : How Social Production Transforms Markets and Freedom (1st ed.). New Haven: Yale University Press.

Berkes, F., and Ross, H. (2013). Community Resilience: Toward an Integrated Approach. Soc. Nat. Resour. 26, 5–20. doi: 10.1080/08941920.2012.736605

Biesta, G. (2015). “Pragmatism and the philosophical foundations of mixed methods research,” in SAGE Handbook of Mixed Methods in Social & Behavioral Research , eds A. Tasahkkori and C. Teddie, (Thousand Oaks: SAGE Publications, Inc), 95–118.

Boer, D., and Fischer, R. (2010). Towards a holistic model of functions of music listening across cultures: A culturally decentred qualitative approach. Psychol. Music 40, 179–200. doi: 10.1177/0305735610381885

Braun, V., and Clarke, V. (2006). Using thematic analysis in psychology. Qual. Res. Psychol. 3, 77–101.

Burles, M., and Bally, J. (2018). Ethical, Practical, and Methodological Considerations for Unobtrusive Qualitative Research About Personal Narratives Shared on the Internet. Int. J. Qual. Methods 17, 1–9. doi: 10.1177/1609406918788203

Burt, R. S. (2005). Brokerage and Closure: An Introduction to Social Capital. New York: Oxford University Press.

Castells, M. (2015). Networks of Outrage and Hope – Social Movements in the Internet age, 2nd edition. Cambridge, UK: Polity Press.

Chen, G. M. (2011). Tweet this: A uses and gratifications perspective on how active Twitter use gratifies a need to connect with others. Comput. Hum. Behav. 27, 755–762. doi: 10.1016/j.chb.2010.10.023

Clayton, M., Jakubowski, K., Eerola, T., Keller, P. E., Camurri, A., Volpe, G., et al. (2020). Interpersonal Entrainment in Music Performance: Theory. Method Model. Music Percept. 38, 136–194. doi: 10.1525/mp.2020.38.2.136

Coleman, J. (1988). Social Capital in the Creation of Human Capital. Am. J. Sociol. 94, S95–S120.

Couldry, N. (2003). Media Rituals: A Critical Approach. New York: Routledge.

Daffern, H., Balmer, K., and Brereton, J. (2021). Singing together yet apart: The experience of UK choir members and facilitators during the Covid-19 pandemic. Front. Psychol. 12:303. doi: 10.3389/fpsyg.2021.624474

De Nora, T. (2000). Music in Everyday Life. Cambridge: Cambridge University Press, doi: 0.1017/CBO9780511489433

de Saint Laurent, C., Glãveanu, V., and Chaudet, C. (2020). Malevolent Creativity and Social Media: Creating Anti-immigration Communities on Twitter. Creat. Res. J. 32, 66–80. doi: 10.1080/10400419.2020.1712164

Devakumar, D., Shannon, G., Bhopal, S., and Abubakar, I. (2020). Racism and discrimination in COVID-19 responses. Lancet 395:1194.

Dewan, S., Ho, Y.-J., and Ramaprasad, J. (2017). Popularity or Proximity: Characterizing the Nature of Social Influence in an Online Music Community. Inform. Syst. Res. 28, 117–136. doi: 10.1287/isre.2016.0654

Dewan, S., and Ramaprasad, J. (2012). Music Blogging, Online Sampling, and the Long Tail. Inform. Syst. Res. 23, 1056–1067. doi: 10.1287/isre.1110.0405

Dingle, G. A., Brander, C., Ballantyne, J., and Baker, F. A. (2013). ‘To be heard’: The social and mental health benefits of choir singing for disadvantaged adults. Psychol. Music 41, 405–421. doi: 10.1177/0305735611430081

Dong, E., Du, H., and Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect. Dis. 20, P533–534. doi: 10.1016/S1473-3099(20)30120-1 published online Feb 19.

Draper, G., and Dingle, G. A. (2021). “It’s not the same”: A comparison of the psychological needs satisfied by musical group activities in face to face and virtual modes. Front. Psychol. 12:303. doi: 10.3389/fpsyg.2021.646292

Dunbar, R. I. M. (2012). “On the evolutionary function of song and dance,” in Music, Language, and Human Evolution , ed. N. Bannan (Oxford: Oxford University Press), 201–214.

Fancourt, D., and Steptoe, A. (2019). Present in Body or Just in Mind: Differences in Social Presence and Emotion Regulation in Live vs. Virtual Singing Experiences. Front. Psychol. 10:778. doi: 10.3389/fpsyg.2019.00778

Good, A., and Russo, F. A. (2016). Singing promotes cooperation in a diverse group of children. Soc. Psychol. 47, 340–344.

Granovetter, M. S. (1973). The Strength of Weak Ties. Am. J. Soc. 78, 1360–1380.

Granovetter, M. S. (1983). The Strength of Weak Ties: A Network Theory Revisited. Soc. Theory 1, 201–233. doi: 10.2307/202051

Grossman, M. (2014). “Resilient multiculturalism? Diversifying Australian approaches to community resilience and cultural difference,” in Global Perspectives on the Politics of Multiculturalism in the 21st Century: A Case Study Analysis , eds F. Mansouri and B. Ebanda de B’béri (London: Routledge), 161–180.

Healy, E., Arunachalam, D., and Mizukami, T. (2016). “Social Cohesion and the Challenge of Globalization,” in Creating Social Cohesion in an Interdependent World , eds E. Healy, D. Arunachalam, and T. Mizukami (New York: Palgrave Macmillan), 3–31.

Hesmondhalgh, D. (2013). Why Music Matters. Chichester: Wiley Blackwell.

Hilbert, M., Vasquez, J., Halpern, D., Valenzuela, S., and Arriagada, E. (2017). One Step, Two Step, Network Step? Complementary Perspectives on Communication Flows in Twittered Citizen Protests. Soc. Sci. Comput. Rev. 35, 444–461. doi: 10.1177/0894439316639561

Jacoby, N., Margulis, E. H., Clayton, M., Hannon, E., Honing, H., Iversen, J., et al. (2020). Cross-Cultural Work in Music Cognition: Challenges. Insights Recommen. Music Percept. 37, 185–195. doi: 10.1525/MP.2020.37.3.185

Koelsch, S. (2013). From social contact to social cohesion—The 7 Cs. Music Med. 5, 204–209. doi: 10.1177/1943862113508588

Kreis, R. S. (2017). #refugeesnotwelcome: Anti-refugee discourse on Twitter. Discour. Commun. 11, 498–514.

Mehr, S. A., Singh, M., Knox, D., Ketter, D. M., Pickens-Jones, D., Atwood, S., et al. (2019). Universality and diversity in human song. Science 366, 1–17. doi: 10.1126/science.aax0868

Mishra, P., and Henriksen, D. (2018). Creativity, Technology and Education: Exploring their Convergence. Netherland: Springer.

Murthy, D., and Sharma, S. (2019). Visualizing YouTube’s Comment Space: Online Hostility as a Networked Phenomena. New Med. Soc. 21, 191–213. doi: 10.1177/1461444818792393

Ng, E. (2020). The Pandemic of Hate is Giving COVID-19 a Helping Hand. Am. J. Trop. Med. Hygiene 102, 1158–1159. doi: 10.4269/ajtmh.20-0285

Oh, D. C. (2018). “Racist Propaganda”: discursive Negotiations on YouTube of Perceived Anti-White Racism in South Korea. Atlantic J. Commun. 26, 306–317. doi: 10.1080/15456870.2018.1517767

Packer, J., and Ballantyne, J. (2011). The impact of music festival attendance on young people’s psychological and social well-being. Psychol. Music. 39, 164–181. doi: 10.1177/0305735610372611

Páez, D., Rimé, B., Basabe, N., Wlodarczyk, A., and Zumeta, L. (2015). Psychosocial Effects of Perceived Emotional Synchrony in Collective Gatherings. J. Person. Soc. Psychol. 108, 711–729. doi: 10.1037/pspi0000014

Pariser, E. (2011). The Filter Bubble: What the Internet is Hiding from You. London: Viking/Penguin press.

Pink, S., Horst, H. A., Postill, J., Hjorth, L., Lewis, T., and Tacchi, J. (2016). Digital Ethnography?: Principles and Practice [electronic resource]. California: SAGE.

Putnam, R. D. (2000). Bowling Alone: The Collapse and Revival of American Community. New York, NY: Simon & Schuster.

Putnam, R. D. (2007). E Pluribus Unum: Diversity and Community in the Twenty-first Century The 2006 Johan Skytte Prize Lecture. Scand. Polit. Stud. 2, 137–174.

QSR International, (1999). NVivo Qualitative Data Analysis Software [Software]. Australia: QSR International.

Rosenbusch, H., Evans, A. M., and Zeelenberg, M. (2019). Multilevel Emotion Transfer on YouTube: Disentangling the Effects of Emotional Contagion and Homophily on Video Audiences. Soc. Psychol. Person. Sci. 10, 1028–1035. doi: 10.1177/1948550618820309

Sajuira, J., van Heerde-Hudson, J., Hudson, D., Dasandi, N., and Theocharis, Y. (2015). Tweeting Alone? An Analysis of Bridging and Bonding Social Capital in Online Networks. Am. Polit. Res. 43, 708–738. doi: 10.1177/1532673X14557942

Salganik, M. J., Dodds, P., and Watts, D. J. (2006). Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market. Science 311, 854–856.

Schäfer, K., and Eerola, T. (2020). How listening to music and engagement with other media provide a sense of belonging: An exploratory study of social surrogacy. Psychol. Music 48, 232–251. doi: 10.1177/0305735618795036

Schäfer, K., Saarikallio, S., and Eerola, T. (2020). Music may reduce loneliness and act as social surrogate for a friend: evidence from an experimental listening study. Music Sci. 3, 1–16. doi: 10.1177/2059204320935709

Slater, M. J., Haslam, S. A., and Steffens, N. K. (2018). Singing it for “us”: Team passion displayed during national anthems is associated with subsequent success. Eur. J. Sport Sci. 18, 541–549. doi: 10.1080/17461391.2018.1431311

UNESCO, (2005). The 2005 Convention for the Protection and Promotion of the Diversity of Cultural Expressions. Paris: UNESCO.

UNESCO, (2017). Operational Guidelines on the Implementation of the Convention the Digital Environment. Paris: UNESCO.

UNESCO, (2020a). Culture in Crisis: Policy guide for a resilient creative sector. Paris: UNESCO.

UNESCO, (2020b). #DontGoViral: UNESCO and i4Policy launch a campaign to crowdsource local content to combat the Infodemic in Africa. Paris: UNESCO.

van der Hoeven, A., and Hitters, E. (2019). The social and cultural values of live music: Sustaining urban live music ecologies. Cities 90, 263–271.

Vougioukalou, S., Dow, R., Bradshaw, L., and Pallant, T. (2019). Wellbeing and integration through community music: The role of improvisation in a music group of refugees, asylum seekers and local community members. Contemp. Music Rev. 38, 1–16. doi: 10.1080/07494467.2019.1684075

Vuoskoski, J. K., Clarke, E. F., and De Nora, T. (2017). Music listening evokes implicit affiliation. Psychol. Music 45, 584–599.

Vuoskoski, J. K., and Eerola, T. (2012). Can sad music really make you sad? Indirect measures of affective states induced by music and autobiographical memories. Psychol. Aesthetics Creat. Arts 6, 204–213.

Weisbuch, M., Pauker, K., and Ambady, N. (2009). The Subtle Transmission of Race Bias via Televised Nonverbal Behavior. Science 326, 1711–1714. doi: 10.1126/science.1178358

Wen, J., Aston, J., Liu, X., and Ying, T. (2020). Effects of misleading media coverage on public health crisis: a case of the 2019 novel coronavirus outbreak in China. Anatolia 31, 331–336. doi: 10.1080/13032917.2020.1730621

Zappavigna, M. (2012). Discourse of Twitter and Social Media: How We Use Language to Create Affiliation on the Web. Chicago, IL: A & C Black.

Keywords : social capital, community resilience, COVID-19, social distancing, collective effervescence, music, bridging, bonding

Citation: Fraser T, Crooke AHD and Davidson JW (2021) “Music Has No Borders”: An Exploratory Study of Audience Engagement With YouTube Music Broadcasts During COVID-19 Lockdown, 2020. Front. Psychol. 12:643893. doi: 10.3389/fpsyg.2021.643893

Received: 19 December 2020; Accepted: 11 June 2021; Published: 08 July 2021.

Reviewed by:

Copyright © 2021 Fraser, Crooke and Davidson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Trisnasari Fraser, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Fifteen years of YouTube scholarly research: knowledge structure, collaborative networks, and trending topics

  • Published: 19 September 2022
  • Volume 82 , pages 12423–12443, ( 2023 )

Cite this article

  • Mohamed M. Mostafa 1 ,
  • Ali Feizollah 2 &
  • Nor Badrul Anuar 2  

3176 Accesses

2 Citations

1 Altmetric

Explore all metrics

Since its inception, YouTube has been a source of entertainment and education. Everyday millions of videos are uploaded to this platform. Researchers have been using YouTube as a source of information in their research. However, there is a lack of bibliometric reports on research carried out on this platform and the pattern in the published works. This study aims at providing a bibliometric analysis on YouTube as a source of information to fill this gap. Specifically, this paper analyzes 1781 articles collected from the Scopus database spanning fifteen years. The analysis revealed that 2006-2007 were initial stage in YouTube research followed by 2008 -2017 which is the decade of rapid growth in YouTube research. The 2017 -2021 is considered the stage of consolidation and stabilization of this research topic. We also discovered that most relevant papers were published in small number of journals such as New Media and Society, Convergence, Journal of Medical Internet Research, Computers in Human Behaviour and the Physics Teacher, which proves the Bradford’s law. USA, Turkey, and UK are the countries with the highest number of publications. We also present network analysis between countries, sources, and authors. Analyzing the keywords resulted in finding the trend in research such as “video sharing” (2010-2018), “web -based learning” (2012-2014), and “COVID -19” (2020 onward). Finally, we used Multiple Correspondence Analysis (MCA) to find the conceptual clusters of research on YouTube. The first cluster is related to user -generated content. The second cluster is about health and medical issues, and the final cluster is on the topic of information quality.

Similar content being viewed by others

youtube music research paper

A Medical Science Educator’s Guide to Selecting a Research Paradigm: Building a Basis for Better Research

Megan E.L. Brown & Angelique N. Dueñas

youtube music research paper

Open peer review: promoting transparency in open science

Dietmar Wolfram, Peiling Wang, … Hyoungjoo Park

youtube music research paper

Social Constructivism—Jerome Bruner

Avoid common mistakes on your manuscript.

1 Introduction

Since its acquisition by Google in 2005, YouTube has been a video -sharing social media and a search engine with over 2 billion views per month [ 41 ]. It allows users to upload videos and share their content. It is a preferred search engine for contents like cooking recipes because of its audio and visual medium of communication. In addition to watching the videos, users can leave their comments and feedbacks for each video. The combination of audio, video, and comments make YouTube a valuable source of data. Researchers have been using this source of data to analyze various topics across wide range of research domains. One of the research domains that utilizes YouTube is health and healthcare. Educational videos and users’ feedback towards them have been a common research topic. For example, Li et al. [ 41 ] examined YouTube as a source of information on COVID -19 pandemic. Khatri et al. [ 34 ] also researched YouTube as a source of information on COVID -19 on English and Mandarin content. Hussein et al. [ 30 ] evaluated YouTube as a source of information by measuring the information on this platform and by auditing misinformation in videos. Indirectly, some research works developed methods that can be used in YouTube video analysis [ 42 , 56 , 57 , 45 ]. Analyzing research trends in YouTube papers requires the use of the bibliometric method.

Bibliometric is a quantitative analysis of papers published in a specific research domain [ 46 ]. The bibliometric study analyzes the authors’ activities, publication trends, and collaborations among institutions and countries. The bibliometric analysis evaluates impact of published papers and reveals the potential gaps and future directions in a research area, which increases interest and attention of researchers and funding bodies. The bibliometric study has been used in many research areas like COVID -19 pandemic [ 26 ], agricultural [ 47 ], accounting [ 50 ], and economic [ 8 ]. The advantages of using a bibliometric study are: 1) reveals important research works in a research domain; 2) helps to discover the gaps need to be addressed by researchers; 3) gives young researchers a holistic view of a research area.

To scrutinize research trends and direction on YouTube, this study aims at performing a bibliometric analysis on research works focused on YouTube published between 2006 and 2021. We propose the following research questions to fulfill the aim of this study: 1) what are the trends and directions in YouTube research? And 2) what information can be discovered related to YouTube research? The contributions of this study are as following:

we found only one published paper on YouTube bibliometric study, which presents number of papers, citations, and countries that published research works related to YouTube [ 56 ]. However, our work presents a more comprehensive analysis of the YouTube papers by providing network analysis, research structure, and thematic mapping.

we present a comprehensive network analysis like co -citation network, co -cited sources network, authors’ collaboration network, institutions’ collaboration network, nations’ network, as well as keywords and co -occurrence network.

We analyze the trending research and provide a structured research trends as well as thematic and historiographic mapping.

we adopt dominance factor, Bradford’s law, and Lotka’s law to analyze the published works using scientific methods.

This article is organized as follows. Section 2 describes the methodology used to carry out the analysis. Section 3 deals with research findings. Section 4 discusses the research findings. The last section deals with research limitations and explores potential avenues for future research.

This study is guided by the following four steps:

Selecting the database and defining the search terms.

Conducting the preliminary statistical analysis.

Performing the bibliometric network analysis.

Performing the conceptual structure, thematic and historiographic mapping.

To conduct the analysis, the R version 4.1 software [ 58 ] was used along with several libraries such as the bibliometrix, wordcloud and ggplot2 . For network visualization, we used the VOSviewer software [ 61 ]. We discuss here the steps outlined above in some detail.

2.1 Database and documents’ extraction

Following Sigala et al. (2021), the Scopus database was selected to conduct the analysis. As the largest database for peer -reviewed journals (Norris & Oppenheim, 2007), Scopus is frequently used by researchers to conduct bibliometric analysis (Cunill et al., 2019; Hassan et al., 2021). Having selected the database, we extracted bibliographic records related to the selected documents, including relevant information about documents’ titles, authors, and keywords. Retrieved documents were then transformed to a plain text format for further filtering and analysis. Choosing a particular type of document for bibliometric analysis has long been the subject of debate [ 51 , 52 ]. For instance, journal articles only have been selected in prior studies (e.g., [ 20 ]), whereas some authors have focused on both books and journal articles (e.g., [ 4 ]), yet others excluded only meeting abstracts, corrections, and editorial material, (e.g., [ 2 ]). Here, we opted for peer -reviewed articles only because such articles “usually undergo a meticulous peer -review process and are generally of high quality” ([ 16 ], p. 206). To avoid false -positive results, only article titles, abstracts and keywords were searched using the terms “YouTube.” Figure 1 plots the search procedure followed to extract the articles used in this analysis. We limited the selection to documents written in English and we chose 2006 as the date of reference because YouTube was launched in 2006.

figure 1

Schematic flowchart of data acquisition and methodology (Adapted from [ 15 ])

Having selected the database, we extracted bibliographic records related to the selected documents, including relevant information about documents’ titles, authors, and keywords. Retrieved documents were then transformed to a plain text format for further filtering and analysis. Choosing a particular type of document for analysis has long been the subject of debate [ 51 , 52 ]. For instance, journal articles only have been selected in prior studies (e.g., [ 20 ]), whereas some authors have focused on both books and journal articles (e.g., [ 4 ]), yet others excluded only meeting abstracts, corrections, and editorial material, (e.g., [ 2 ]). Here, we opted for peer -reviewed articles only because such articles “usually undergo a meticulous peer -review process and are generally of high quality” ([ 16 ], p. 206).

Table 1 shows the main information about the YouTube research data.

The table reveals that 1781 research articles were extracted. The articles were written by 4699 authors, and they include 65,677 references. 417 articles were written by single authors, whereas 567 were written by multi -authors, with a collaboration index of 3.26. This index is calculated by dividing the total authors of multi -authored articles by total multi -authored articles [ 23 , 36 ]. Our result indicates that the average YouTube research team falls between 3 and 4.

2.2 Bibliometric network analysis

A network can be regarded as “a structure composed of a set of actors, some of whose members are connected by a set of one or more relationships” ([ 35 ], p. 8). In social network analysis (SNA), an edge connecting two nodes represents a relationship. Khan and Wood [ 32 ] noted that “when used to synthesize the existing literature from a network perspective, the SNA technique can reveal valuable invisible patterns that can certainly facilitate theory development and uncover areas for future research.” There has been extensive prior research using network analysis in areas as diverse as exploring individual scientific collaboration networks [ 11 , 27 , 66 ], collaboration among research institutions [ 21 ] and keywords co -occurrence networks [ 7 ].

2.3 Thematic and conceptual structure maps

Thematic maps or strategic diagrams were suggested by Law et al. [ 39 ]. The map is usually employed to reveal the clusters’ dynamics based on analyzing the keywords or co -word occurrences [ 29 ]. The Callon et al. [ 10 ] density and centrality metrics are generally used to construct the map. The map also draws heavily on the financial portfolio analysis and concepts based on co -word networks [ 5 ]. Due to its usefulness, the map has been used in a plethora of research articles [ 33 , 40 , 65 ]. On the other hand, conceptual structure maps can be employed to investigate the conceptual structure of a research area by breaking down a research domain into clear “knowledge clusters” [ 63 ].

3.1 Scientific output, core journals and impactful authors

We extracted 1781 Scopus documents related to YouTube. The documents were written by 4699 authors representing 70 nations. Timewise, the documents covered almost fifteen years (2006-2021). Figure 2 plots the scientific output trends in the field. Although the figure reveals an exponential annual growth rate, this rate is not evenly distributed. For instance, in the first two years there was a paucity in YouTube research with only a handful of papers per year. These two years might be referred to as “the initial stage in the YouTube research.” However, the next decade (2008-2017) appears to witness a tremendous increase in research dealing with YouTube. This decade might be called “the rapid growth stage.” Indeed, this period represents the highest growth rate. The final stage (2018-2021) might be called the “consolidation and stabilization stage” because the YouTube research reached the “saturation/maturity” stage. This result is in line with several bibliometric studies conducted in several research areas [ 53 , 66 ].

figure 2

YouTube research annual scientific production (2006–2021)

Table 2 shows the most important Scopus -indexed journals publishing YouTube research. The table reveals that the most relevant sources publishing YouTube research include journals such as New Media and Society, Convergence, Journal of Medical Internet Research, Computers in Human Behavior and the Physics Teacher . Another way to examine the journals’ influence is known as the Bradford’s law [ 37 ]. This law was first proposed by Bradford [ 9 ], who noted that “if scientific journals are arranged in order of decreasing productivity of articles on a given subject, they may be divided into a nucleus of periodicals more particularly devoted to the subject and several groups or zones containing the same number of articles as the nucleus.” Fig.  3 plots the Bradford’s law in YouTube research. From the graph, we see that the “core zone” is dominated by just few journals, including New Media and Society, Convergence, Journal of Medical Internet Research, etc. Such journals are considered the outlets publishing the “core” YouTube research.

figure 3

Bradford’s law in YouTube scholarly research

The YouTube research growth is also evident from the corresponding author’s country involved (Fig.  4 ).

figure 4

YouTube research by corresponding author’s country. Note: SCP = Single Country Production; MCP = Multiple Country Production

Table 3 shows the most cited articles in YouTube research. The table shows that Smith et al. (2012) paper in the Journal of Interactive Marketing is the most cited paper as it was cited 457 times. In this article, the authors compared brand -related user -generated content between three social media platforms, namely Twitter, Facebook, and YouTube. Results provide a general theoretical framework demonstrating how consumer -generated brand communications are influenced by a particular social media channel. The second most cited paper (443 citations) is Lang (2007) paper published in the Journal of Computer - Mediated Communication. In this paper, the author employed ethnographic methodology to analyze how YouTube participants develop and maintain social networks related to video sharing activities. With 333 citations, Susarla et al. (2011) article is the third most cited paper. In this article published in Information Systems Research , the authors analyzed the networked structure of interactions on YouTube. Results revealed that “social interactions are influential not only in determining which videos become successful but also on the magnitude of the impact.” (p. 23). Halpern and Gibbs (2013) paper published in Computers in Human Behavior was cited 298 times. In this paper the authors used two social media platforms, namely YouTube and Facebook to examine how social media can be used to foster democratic deliberations. Results showed that the “Facebook expands the flow of information to other networks and enables more symmetrical conversations among users, whereas politeness is lower in the more anonymous and deindividuated YouTube” (p. 1159). Khan’s (2017) paper published in Computers in Human Behavior was cited 291 times. In this paper the author investigated motives behind YouTube users’ engagement. Results revealed that YouTube participation is driven mainly by the relaxing/entertainment motive. However, passive content viewing was mainly driven by reading comments posted on the platform. Table 4 .

The dominance factor is a bibliometric measure that calculates authors dominance by dividing the number of multi -authored articles in which the author is the first author by the total number of multi -authored articles [ 38 ]. This metric has been used widely in the literature [ 23 , 25 ]. Figure 5 shows the dominating authors over time. From the figure, we see that the most dominating authors were C Basch from 2015 till 2021, Riendeau from 2009 till 2012 and S Azer from 2012 to 2021. Newcomers to the field have also achieved some dominance. Examples include J Yin (2017-2019) and J Park (2016-2021).

figure 5

YouTube authors dominance over the time

In bibliometric studies, “Evenness/concentration of authors’ contribution” is a widely used metric [ 49 ]. This metric can be quantified using Lotka’s law (Lotka, 1926). Based on the well -known Zipf’s law, Lotka’s law implies that “the number of authors producing a certain number of articles is a fixed ratio, 2, to single -article authors.” Results suggests that the Lotka’s law seems to hold in YouTube research ( K - S two sample test p  > 0.05).

3.2 Network analysis

3.2.1 co -citation networks.

A co -citation network is formed when two authors are cited together in a third reference. Figure 6 displays the YouTube research co -cited authors’ network. Based on the color used, the graph reveals four distinct clusters. The red cluster includes authors such as J Burgess, M Thelwall and J Green. The size of the node indicates which author occupies a central position in the cluster. Such author(s) might be regarded as influential as they have disproportionate impact on the information diffusion on the network [ 6 ]. From the graph, we also see that some nodes are quite close to each other, whereas others drift further away. McPherson et al. [ 48 ] argued that closeness signifies a strong “homophily effect,” which occurs when authors in a virtual -room -like environment discuss common topics [ 24 ]. In bibliometrics, homophily is an indicator of “disciplinary or thematic similarity” [ 31 ]. For example, the nodes representing both R Schatz and A Finamore are very close to each other, indicating possible “homophily effect.”

figure 6

YouTube authors co-citation network (> = 30 articles)

The green cluster includes authors such as C Basch, J Keelan, A Pandy and S Sarangi. The blue cluster includes sixty -two authors such as J Baker, D Charnock, A Rapp and J Lee. The yellow cluster is the smallest and it includes ten authors such as A Finamore, R Schatz and J Wang. The centrally located authors in each cluster might be regarded as influential authors as they “tend to anchor each community and they have a large impact on other communities as they control and stimulate information diffusion [in the network] through research activities” ([ 53 ], p. 664).

Figure 7 displays the YouTube research co -cited sources’ network. The graph reveals five distinct clusters. For example, the Journal of Clinical Rheumatology, Epilepsy Behavior and the Journal of Cancer Education are co -cited together as they belong to the same cluster. The American Sociological Review is co -cited with Discourse and Society, and Feminist Media Studies . The Journal of Advertising is co -cited with the Journal of Business Research and the Journal of Consumer Research , whereas Body Image is co -cited with the Journal of Pragmatics and Sex Roles . Interestingly, “core” journals occupy central position in the network with a minimal interaction among the distinct clusters, confirming what Glotzl and Aigner [ 28 ] term “the orthodox core -heterodox periphery” phenomenon within the field of YouTube research. Dobusch and Kapeller [ 22 ] found that “orthodox journals” tend to be heavily cited, whereas “heterodox journals” tend to be drifted towards the periphery.

figure 7

YouTube source co-citation network (> = 30 articles)

3.2.2 Collaboration networks

The collaboration network among authors is depicted in Fig.  8 . The thickness of the link in this graph is proportionate to articles coauthored, whereas the node size is formed based on the author’s publications. A glance at the graph reveals that the sparse network is formed by seven distinct communities, signifying a limited cooperation among authors. The sparse network implies that impactful researchers in the field work in isolated “silos” [ 62 ].

figure 8

YouTube authors’ collaboration network (documents > = 2 articles)

Figure 9 depicts the collaboration network at the institutional level. The thickness of the link is proportional to the institution’s collaboration, whereas the node size is formed based on each institution’s publications. From the graph, we see that there are seven distinct clusters. For example, there is a strong collaboration between Columbia University, the New York University and the William Paterson University in the US. Zou et al. [ 66 ] argued that this type of sparse collaboration reflects a “locally -centralized -globally -discrete” cooperation. It also reflects a “North -South” divide, with a clear lack of cooperation between developed/developing world institutions.

figure 9

Collaboration network among institutions producing YouTube research (documents > = 1 article)

Figure 10 shows the collaboration at the nations’ level, with a total of 62 nations collaborating in the scientific production of YouTube research. The figure shows that US tops the world in terms of the total collaboration links, followed by the UK and Australia. A closer look at the graph reveals that some clusters are formed based on geographic distance or linguistic similarity. For example, Spain cooperates with Colombia, Ecuador and Mexico. The cluster that includes Egypt also includes Kuwait and Saudi Arabia. Figure 11 plots the “geographic atlas” of the countries producing the YouTube research.

figure 10

Collaboration network among nations producing YouTube scholarly research (documents > = 2 articles)

figure 11

Geographic atlas of collaboration among nations producing YouTube scholarly research

3.2.3 Keywords and co -occurrence network analysis

Due to their abstract nature [ 12 ], keywords can be used to reveal the content of a paper. Figure 12 shows a simple wordcloud constructed based on the author -provided keywords. A wordcloud plot is an appealing visual tool that can be used to summarize textual data. The size of each word and its closeness to the cloud center determine its significance [ 42 , 43 ]. From the figure we see that the most relevant/frequent keywords used are “Youtube”, “social media” and “Internet.”

figure 12

Keyword-based wordcloud of the most frequent YouTube terms

To further scrutinize how frequently keywords co -occur in the same document, we also used the author -provided keywords to construct the YouTube keyword co -occurrence network because “authors of a paper should be the ones that have the best feel as to what areas are spoken to by the paper” [ 19 ]. Figure 13 displays the resulting co -occurrence network. The graph reveals eight main clusters. For example, the first cluster in blue deals with medical/health use of the YouTube and includes words such as “health communication”, “health education” and “health information”. The second cluster (green -colored) deals with consumer comments and includes words such as “user -generated content”, “social network” and “Web 2.0”. The third cluster (yellow -colored) deals mainly with the educational use of the YouTube and includes words such as “e -learning”, “medical education” and “online videos”.

figure 13

Co-occurrence network for author-provided YouTube keywords

A three -field plot, also known as a Sankey diagram, was also used to contextualize the flow trend linking keywords (left), authors (middle) and sources (right). In this diagram the size of the boxes is proportional to the related quantity (keyword, author, or source). Figure 14 displays the YouTube research Sankey diagram. Not surprisingly, edge widths flowing from keywords as “YouTube”, “social media”, and “Internet” are the largest, signifying that such keywords were used by several authors in their publications. We see also see that while some authors have used an extensive list of the keywords reflecting the diversity of their research (C Basch), others used a unique keyword (J Kim).

figure 14

Sankey diagram for YouTube research flow (kewword-author-reference)

3.2.4 Trending topics and thematic evolution

Figure 15 plots the major YouTube research trending topics. From the graph we see that there is a move from established YouTube topics such as “video sharing” (2010-2018) and “web -based learning” (2012-2014) to new topics such as “COVID -19” (2020 onwards) and “misinformation” (2020 onwards). Such topics might be regarded as “trending topics/hotspots” in the scholarly publications dealing with YouTube because it has been argued that trending topics usually represent hotspots or evolving themes in a specific research domain [ 13 , 14 , 54 , 60 ]. Abrupt burst or surge in keywords might be also an indicator of “potential fronts” [ 57 ] as “the body of knowledge in a certain discipline can be seen as a sequence of topics that appear, grow in importance for a particular period and then disappear” [ 18 ].

figure 15

YouTube research trending topics

3.3 Conceptual structure and thematic maps

We applied the Multiple Correspondence Analysis (MCA) method on the author -provided keywords. The MCA is an extension of correspondence analysis, akin to the Principal Component Analysis (PCA), that helps to analyze the pattern of relationships of categorical data [ 1 ]. It was selected since the results of this method is proved to be better on categorical data compared to other methods [ 1 ]. Figure 16 depicts the resulting YouTube research conceptual structure over four decades. From the graph, we see that the best dimension reduction achieved for the first two dimensions of the MCA account for roughly 72% of the total variability. In this graph, the closer the dots, the similar the profile they represent, whereas each cluster of dots represents discriminating profiles [ 64 ].

figure 16

Conceptual structure map for YouTube scholarly research (MCA method)

An inspection of the graph reveals the depth and breadth of the domain. For instance, the largest red cluster comprises keywords emphasizing the consumer -generated content such as “user -generated content”, “web 2.0” and “online video.” The second cluster (in green) appears to deal with health and medical issues and includes keywords such as “health communication”, “health information” and “misinformation.” The third cluster in blue appears to deal with YouTube research within the context of information quality and includes keywords such as “internet”, “information” and “quality.”

A thematic/strategic map is also shown in Fig.  17 . In this graph, average values of both axes are represented by a dotted line dividing the map into four quadrants. Each quadrant in this graph represents a different theme, whereas the bubble size is drawn in proportion to the frequency of documents in which the keywords is used. The first quadrant represents “motor themes” that are well -developed both internally and externally as it is characterized by high density and centrality. [ 17 ]. Within the YouTube research, such themes include “user -generated content”, “new media”, “influencers”, and “gender.” The second one is usually labeled the “highly -developed -and -isolated themes” quadrant as it deals with niche themes. With high -density -low -centrality structure, this quadrant highlights the fact that while the themes it comprises are well -developed internally, they are marginally important externally. Within the YouTube research, such themes include “education,” “medical education”, and “technology.” The low -density -low -centrality third quadrant is termed the “emerging -or -declining themes” quadrant. This implies that the themes in this quadrant are characterized by weak ties at the internal and external levels. Such themes might indicate potential hotspots in YouTube research. Examples include “COVID -19”, “health communication” and “Twitter.” Finally, the “basic -and -transversal themes” quadrant (low density -high -centrality) comprises themes that are weakly developed in terms of internal ties. Nevertheless, they are characterized by important external ties. Within the YouTube research, such themes include “Social media” and “internet.”

figure 17

YouTube research thematic/strategic map

4 Discussion

This study examined published research works related to YouTube between 2006 and 2021. At this point, we can answer the research questions. To answer the first research question about trends and directions, we found that between 2006 and 2008, there was a slow growth in publications since the YouTube platform was new. Then from 2008 to 2017, there was a rapid growth in research on YouTube. Afterwards, the trend is still upward with a slower pace. We also found that the trending topic changes over time. While “gaming” and “video sharing” were trending topics in some time period, the trend shifted towards topics like “COVID -19” and “misinformation”.

The second research question is related to the information discovered from YouTube research. We discovered the most cited papers, authors, and countries with highest number of publications. We also discovered the network between the published works. Specifically, the authors’ collaboration network, collaboration between institutions, and collaboration between countries. We also analyzed the collected works regarding the Bradford’s law and Lotka’s law. It was proved that large number of papers were published in a small group of journals, which followed the Bradford’s law. Also, it was proved that the frequency indexes of author productivity distribution followed Lotka’s law. Additionally, the MCA algorithm was used to find the conceptual structure map related to YouTube papers. The output shows three clusters, consumer -generated content, health and medical issues, and information quality.

Based on this paper’s results, large number of works are related to health and medical issues. Among the institutions, department of public health appeared more than other institutions. Additionally, the journal of medical internet research is in the third spot of the most relevant sources. The MCA algorithm dedicated one cluster for health and medical issues. Furthermore, “medical education” topic started trending in 2014 and is still trending, based on Fig.  15 , which is one of the longest trending topics. It is clear that researchers are interested in analyzing YouTube about health -related issues. These points coincide with studies on effectiveness of YouTube videos as a health educational platform. Allgaier mentioned that many people use YouTube as a source of information on science, technology, and health [ 3 ]. It is also assumed that because of the sensitivity of health and medical related issues, researchers focused more on the health aspect of the YouTube to find information and misinformation in videos. They analyzed videos and comments to understand users’ feedback on the health -related videos [ 59 ].

5 Limitations and future research

Despite the major contributions of this study, it suffers from some limitations. First, we relied only on the Scopus database to conduct our bibliometric analysis. Thus, we unavoidably commit a selection bias. Subsequently, we believe that future research should test the robustness of our finding by merging several databases such as WoS and Google Scholar. However, it has been argued that the Google Scholar database is less stringent as it comprises citations from unpublished manuscripts, blogs, etc. (Gavel & Iselid, 2008; [ 55 ]). Second, we limited the selection of documents to articles published in English. Thus, our results might be limited in terms of coverage [ 57 ]. Future research might add other languages to test the generalizability of our findings. Finally, although we conducted a comprehensive study on the whole domain of YouTube research, future research might focus on specific journals publishing YouTube research such as New Media and Society, Convergence, Journal of Medical Internet Research, Computers in Human Behaviour, and the Physics Teacher, among others.

6 Conclusion

This work conducted a bibliometric study on YouTube, as a research topic, in the literature between 2006 and 2021. The search in Scopus database resulted in 1781 research works, which were collected along their meta data such as authors name, keywork, etc. The collected data were analyzed, and the results were presented in the form of network of collaborations between authors, institutions, and countries. We also show the results of networks of keywords. We then created a thematic map based on the keywords to find the trending topic in research related to YouTube. The analysis revealed that 2006 -2007 were initial stage in YouTube research followed by 2008 -2017 which is the decade of rapid growth in YouTube research. The 2017 -2021 is considered the stage of consolidation and stabilization of this research topic. We also found that the trending topic changes over time. While “gaming” and “video sharing” were initially trending, the trend shifted towards topics like “COVID -19” and “misinformation”.

Abdi H, Valentin D (2007) Multiple correspondence analysis. Encycl Meas Stat 2(4):651–657

Google Scholar  

Al-Khalifa H (2014) Scientometric assessment of Saudi publication productivity in computer science in the period of 1978-2012. Int J Web Inf Syst 10:194–208

Allgaier J (2019) Science and environmental communication on YouTube: strategically distorted Communications in Online Videos on climate change and climate engineering. Front Commun 4(36):1–14. https://doi.org/10.3389/fcomm.2019.00036

Article   Google Scholar  

Aryadoust V, Ang B (Forthcoming) Exploring the frontiers of eye tracking research in language studies: A novel co-citation scientometric review. Comput Assist Lang Learn

Ávila-Robinson A, Wakabayashi N (2018) Changes in the structures and directions of destination management and marketing research: A bibliometric mapping study, 2005-2016. J Destin Mark Manag 10:101–111

Bakshy E, Hofman J, Mason W, Watts D (2011) Everyone’s an influencer. In: King I, Nejdl W, Li H (eds) Proceedings of the 4th ACM International conference on web search and data mining – WSDM’11. ACM Press, New York, p 65

Banckendorff P (2009) Themes and trends in Australian and New Zealand tourism research: A social network analysis of citations in two leading journals (1994-2007). J Hosp Tour Manag 16:1–15

Bonilla CA, Merigó JM, Torres-Abad C (2015) Economics in Latin America: a bibliometric analysis. Scientometrics 105(2):1239–1252. https://doi.org/10.1007/s11192-015-1747-7

Bradford S (1934) Sources of information on specific subjects. Eng Illus Wkly J 137:85–86

Callon M, Courtial J, Laville F (1991) Co-word analysis as a tool for describing the network of interactions between basic and technological research: the case of polymer chemistry. Scientometrics 22:155–205

Chen X, Liu Y (2020) Visualization analysis of high-speed railway research based on CiteSpace. Transp Policy 85:1–17

Chen C, Song I, Yuan X, Zhang J (2008) The thematic and citation landscape of data and knowledge engineering (1985-2007). Data Knowl Eng 67:234–250

Chen C, Hu Z, Liu S, Tseng H (2012) Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opin Biol Ther 12:593–608

Chen C, Dublin R, Kim M (2014) Orphan drugs and rare diseases: A scientometric review (2000-2014). Expert Opin Orphan Drugs 2:709–724

Chen X, Zou D, Cheng G, Xie H (2020) Detecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & education. Comput Educ 151:103855

Chen X, Zou D, Xie H, Cheng G (2021) Twenty years of personalized language learning: topic modeling and knowledge mapping. Educ Technol Soc 24:205–222

Cobo M, Lopez-Herrera A, Herrera-Viedma E, Herrera F (2011) An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. J Inflametrics 5:146–166

Colicchia C, Creazza A, Noe C, Strozzi F (2019) Information sharing in supply chains: A review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Manag 24:5–21

Corbet S, Dowling M, Gao X, Huang S, Lucey B, Vigne S (2019) An analysis of the intellectual structure of research on financial economics of precious metals. Res Policy 63(101416):101416

Corte V, Gaudio G, Sepe F (2018) Ethical food and the kosher certification: A literature review. Br Food J 120:2270–2288

Ding Y (2011) Scientific collaboration and endorsement: network analysis of co-authorship and citation networks. J Inflamm 5:187–203

Dobusch L, Kapeller J (2012) A guide to paradigmatic self-marginalization: lessons for post-Keynesian economists. Rev Polit Econ 24:469–487

Elango B, Rajendran P (2012) Authorship trends and collaboration pattern in the marine sciences literature: A scientometric study. Int J Inf Dissem Technol 2:166–169

Findlay K, van Rensburg O (2018) Using interaction networks to map communities on twitter. Int J Mark Res 60:169–189

Firdaus A, Ab Razak M, Feizollah A, Hashem I, Hazim M, Anuar N (2019) The rise of “blockchain”: bibliometric analysis of blockchain study. Scientometrics 120:1289–1331

Gautam P, Maheshwari S, Kaushal-Deep SM, Bhat AR, Jaggi CK (2020) COVID-19: A bibliometric analysis and insights. Int J Math Eng Manag Sci 5(6):1156–1169

Glänzel W, Schubert A (2005) Analyzing scientific networks through co-authorship. In: Moed H, Glanzel W, Schmoch U (eds) Handbook of Quantitative Science and Technology Research: The Use of Publication and Patent Statistics in Studies of S&T Systems. Springer, Dordrecht

Glotzl F, Aigner E (2018) Orthodox core-heterodox periphery? Contrasting citation networks of economics departments in Vienna. Rev Polit Econ 30:210–240

Gonzales-Valiente C (2019) Redes de citación de revistas iberoamericanas de bibliotecología y ciencia de la información en Scopus. Bibliotecas Anales de Investigación 15:83–98

Hussein E, Juneja P, Mitra T (2020) Measuring misinformation in video search platforms: An audit study on YouTube. Proc ACM Human-Comput Interact 4(CSCW1):Article 048. https://doi.org/10.1145/3392854

Jiang Y, Ritchie B, Benckendorff P (2019) Bibliometric visualization: An application to tourism crisis and disaster research. Curr Issue Tour 22:1925–1957

Khan G, Wood J (2016) Knowledge networks of the information technology management domain: A social network analysis approach. Commun Assoc Inf Syst 39:367–397

Khasseh A, Soheili F, Moghaddam N, Chelak A (2017) Intellectual structure of knowledge in iMetrivs: A co-word analysis. Inf Process Manag 53:705–720

Khatri P, Singh SR, Belani NK, Yeong YL, Lohan R, Lim YW, Teo WZY (2020) YouTube as source of information on 2019 novel coronavirus outbreak: a cross sectional study of English and mandarin content. Travel Med Infect Dis 35:101636. https://doi.org/10.1016/j.tmaid.2020.101636

Knoke D, Yang S (2010) Social network analysis. SAGE, Los Angeles

Koseoglu M (2016) Mapping the institutional cpollaboration network of strategic management research: 1980-2014. Scientometrics 109:203–226

Kumar H, Dora M (2011) Citation analysis of doctoral dissertations at IIMA: A review of the local use of journals. Libr Collect Acquis Tech Serv 35:32–39

Kumar S, Kumar S (2008) Collaboration in research productivity in oil seed research institutes of India. Fourth International conference on webometrics, informatics and Scientometrics. Universitat zu Berlin, Institute for Library and Information Science, 1-18

Law J, Bauin S, Courtial J, Wittaker J (1988) Policy and the mapping of scientific change: A co-word analysis of research into environmental acidification. Scientometrics 14:251–264

Lee M, Chen T (2012) Revealing research themes and trends in knowledge management: from 1995 to 2010. Knowl-Based Syst 28:47–58

Li HO-Y, Bailey A, Huynh D, Chan J (2020) YouTube as a source of information on COVID-19: a pandemic of misinformation? BMJ Glob Health 5(5):e002604. https://doi.org/10.1136/bmjgh-2020-002604

Liao H, Tang M, Li Z, Lev B (2019a) Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on essential science indicators. Omega 88:228–236

Liao X, Yu Y, Li B, Li Z, Qin Z (2019b) A new payload partition strategy in color image steganography. IEEE Trans Circ Sys Video Technol 30(3):685–696

Liao X, Li K, Zhu X, Liu KR (2020a) Robust detection of image operator chain with two-stream convolutional neural network. IEEE J Sel Top Signal Process 14(5):955–968

Liao X, Yin J, Chen M, Qin Z (2020b) Adaptive payload distribution in multiple images steganography based on image texture features. IEEE Trans on Dependable Secure Comput 1

Liu J, Tian J, Kong X, Lee I, Xia F (2019) Two decades of information systems: a bibliometric review. Scientometrics 118(2):617–643

Luo J, Han H, Jia F, Dong H (2020) Agricultural Co-operatives in the western world: A bibliometric analysis. J Clean Prod 273:122945. https://doi.org/10.1016/j.jclepro.2020.122945

McPherson M, Smith-Lovin L, Cook J (2001) Birds of feather: Homophily in social networks. Annu Rev Sociol 27:415–444

Merediz-Sola I, Bariviera A (2019) A bibliometric analysis of bitcoin scientific production. Res Int Bus Financ 50:294–305

Merigó JM, Yang J-B (2017) Accounting research: A bibliometric analysis. Aust Account Rev 27(1):71–100. https://doi.org/10.1111/auar.12109

Mostafa M (2015) Do products’ warning labels affect consumer safe behavior? A meta-analysis of the empirical evidence. J Bus Econ Stud 22:24–39

Mostafa M (2016) Do consumers recall products’ warning labels? A meta-analysis. Int J Manag Mark Res 9:81–96

Mostafa M (2020) A knowledge domain visualization review of thirty years of halal food research: themes, trends, and knowledge structure. Trends Food Sci Technol 99:660–677

Neff M, Corley E (2009) 35 years and 160,000 articles: A bibliometric exploration of the evolution of ecology. Scientometrics 80:657–682

Neuhaus C, Neuhaus E, Asher A, Wrede C (2006) The depth and breadth of Google scholar: an empirical study. Libr Acad 6:127–141

Noruzi A (2017) YouTube in scientific research: A bibliometric analysis. Webology 14(1):1–7

Qian J, Law R, Wei J (2019) Knowledge mapping in travel website studies: A scientometric review. Scand J Hosp Tour 19:192–209

R Development Core Team (2021) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna https://www.R-project.org

Teng S, Khong KW, Pahlevan Sharif S, Ahmed A (2020) YouTube video comments on healthy eating: descriptive and predictive analysis. JMIR Public Health Surveill 6(4):e19618–e19618. https://doi.org/10.2196/19618

van Eck N, Waltman L (2014) CitNetExplorer: A new software tool for analyzing and visualizing citation networks. J Inf Secur 8:802–823

van Eck N, Waltman L (2019) VOSviewer, version 1.6.13

Vidgen R, Henneberg S, Naude P (2007) What sort of community is the European conference on information systems? A social network analysis 1993-2005. Eur J Inf Syst 22:317–335

Wetzstein A, Feisel E, Hartmann E, Benton W (Forthcoming) Uncovering the supplier selection knowledge structure: A systematic citation network analysis from 1991 to 2017. J Purch Supply Manag

Wong W, Mittas N, Arvanitou E, Li Y (2021) A bibliometric assessment of software engineering themes. Schools and institutions (2013-2020). J Syst Softw 180:111029

Zong Q, Shen H, Yuan Q, Hu X, Hou Z, Deng S (2013) Doctoral dissertations of library and information science in China: A co-word analysis. Scientometrics 94:781–799

Zou X, Yue W, Vu H (2018) Visualization and analysis of mapping knowledge domain of road safety. Accid Anal Prev 118:131–145

Download references

Author information

Authors and affiliations.

Gulf University for Science and Technology, Mubarak Al-Abdullah, West Mishref, Kuwait

Mohamed M. Mostafa

Department of Computer System & Technology, Faculty of Computer Science & Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

Ali Feizollah & Nor Badrul Anuar

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Mohamed M. Mostafa .

Ethics declarations

Competing interests.

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Mostafa, M.M., Feizollah, A. & Anuar, N.B. Fifteen years of YouTube scholarly research: knowledge structure, collaborative networks, and trending topics. Multimed Tools Appl 82 , 12423–12443 (2023). https://doi.org/10.1007/s11042-022-13908-7

Download citation

Received : 13 December 2021

Revised : 21 February 2022

Accepted : 12 September 2022

Published : 19 September 2022

Issue Date : March 2023

DOI : https://doi.org/10.1007/s11042-022-13908-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Bibliometric analysis
  • Co -citation networks
  • Keyword co -occurrence networks
  • Find a journal
  • Publish with us
  • Track your research

To read this content please select one of the options below:

Please note you do not have access to teaching notes, music videos on youtube: exploring participatory culture on social media.

Symbolic Interactionist Takes on Music

ISBN : 978-1-78635-048-0 , eISBN : 978-1-78635-047-3

Publication date: 1 October 2016

The body of scholarship on YouTube is an expanding area of scholarly inquiry. Existent research indicates that music videos are one of the most salient features of YouTube. Interactionist research about popular music has provided important insights through interviews with fans and audience members; however, this work has yet to examine audience engagement with music videos on YouTube. Using Qualitative Media Analysis, I illustrate how the researcher of popular music can work with user comments collected from YouTube. Thematic understandings largely consistent with nostalgia that emerged from an analysis of user-generated comments in response to selected music videos on YouTube are explored. I conclude by suggesting some directions for future research.

  • Social media
  • Qualitative media analysis



Thanks to Joe Kotarba for his tireless efforts to advance the interactionist study of music; and thanks to Isabel Scheuneman Scott for her helpful comments on an earlier draft of this paper. Additionally, I am grateful to the participants of the 2014 Couch-Stone Symposium; and to T.K. Johnson for helping me to think through some of the ideas presented in this paper.

Schneider, C.J. (2016), "Music Videos on YouTube: Exploring Participatory Culture on Social Media", Symbolic Interactionist Takes on Music ( Studies in Symbolic Interaction, Vol. 47 ), Emerald Group Publishing Limited, Leeds, pp. 97-117. https://doi.org/10.1108/S0163-239620160000047016

Emerald Group Publishing Limited

Copyright © 2016 Emerald Group Publishing Limited

We’re listening — tell us what you think

Something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • Front Psychol

Music and neuroscience research for mental health, cognition, and development: Ways forward

Maria agapaki.

1 Department of Early Childhood Education and Care, Oslo Metropolitan University, Oslo, Norway

Elizabeth A. Pinkerton

2 Independent Researcher, Dubai, United Arab Emirates

Efthymios Papatzikis


The brain function on music has been a recently developing field of neuroscience that holds a position of great interest to neuroscientists, psychologists, health professionals, and musicians alike. The primary goal of investigating music and the brain has been to determine particular neural correlates that are involved in or altered by the engagement of humans with music. It can be said that the study of the neuroscience behind music is a discussion regarding human behavior, environmental stimuli, and how that can be represented in our physiology, as well as how our brain structure allows us to interact with such stimuli in a unique and functional way.

Music is a complex phenomenon that employs, from very early in life, widespread neural activity in interconnected regions of sensory perception (Papatzikis et al., 2019 ), and ranging from the auditory cortex (Brattico et al., 2006 ; Allen et al., 2017 ) to the motor system (Furukawa et al., 2017 ; Bashwiner and Bacon, 2019 ) during active and passive music listening or instrument training. By the same token, the music's impact has been greatly correlated to both ontogenetic and phylogenetic neuroplastic changes (Papatzikis and Rishoni, 2022 ), showcasing a strong link to human brain function proven through a plethora of neuroimaging modalities [please see for example (Lin et al., 2010 ; Cross and Fujioka, 2019 ) for EEG/ERP studies; (Donnay et al., 2014 ) for fMRI; (Chacon-Castano et al., 2017 ) for MEG; (Moore et al., 2014 ) for DTI; (Sluming et al., 2002 ) for Voxel-based Morphometry]. However, emerging data suggest that the association between music and the brain is markedly more intricate than simply the response to sensory stimuli. For instance, music has been implicated in contexts of emotional, social, cultural, and biological influence (Peretz, 2006 ; Koelsch, 2018 ; Savage, 2019 ; Savage et al., 2020 ). Developmental neuroscience has studied the processing and perception of music in the fetal and infant brain and its selective role in environmental enrichment and socioemotional development (Papatzikis and Papatziki, 2016 ; Chorna et al., 2019 ; Arrasmith, 2020 ; Papatzikis et al., 2021 ). Mental health research suggests the potential benefits of music in alleviating symptoms in a variety of neurological and affective disorders ranging from depression and schizophrenia to dementia (Van de Winckel et al., 2004 ; Talwar et al., 2006 ; Lin et al., 2011 ; Gustavson et al., 2021 ). Cognitive studies of attention have even observed executive system efficiency differences when comparing the attentional network test (ANT) scores of the alerting and orienting networks of musicians and non-musicians (Medina and Barraza, 2019 ).

Considering music research encompasses a plethora of fields in psychology and neuroscience, and that the current advancements in neuroimaging technologies have made research questions of interest in the field substantially more feasible and diversified, our investigations require a sufficient foundation of quality and validity that ensures the field to move in an effective progression. The assessment of the primary qualitative and quantitative studies that drive the field forward is a necessary systematic review to acknowledge and evade issues like bias, inadequate methodology, or a reproducibility crisis. Previous exemplary studies of the analysis of research quality in other various fields have summarized challenges and subsequent directions, as in the field of population neuroscience (Paus, 2010 ), or have even provided guidelines to address future studies, as in the field of the neuroscience of information systems (Brocke and Liang, 2014 ). Both approaches advocate such consideration to obtain and maximize the potential of neuroscience research.

Therefore, the quality and logistics of research are significant factors that must be adequately regulated to set a standardized precedent for future experimentation within the field. Without doing so, research in music and neuroscience enables the risk of error, bias, and deficient methodology which, in turn, impedes the progression of the field. For instance, in the field of behavioral neuroscience, Bespalov and Steckler ( 2018 ) suggest a current lack of quality control sparked by criticisms regarding poor design, misreporting, and lack of power. Recognizing that the alternative for inadequate research quality would be that which is credible and valuable, it can be implied there are two possible directions for the neuroscience of music. What current research indicates might give us an understanding of which direction that would be, as well as what to do to avoid such devaluation, further justifying the importance of such quality studies.

The current debate

A great and controversial discussion referring to whether and under what conditions music is involved in the intricate network of cognition, emotional regulation, autonomic activity, behavioral and psychophysiological responses, and ultimately in people's mental health (Lin et al., 2011 ) has emerged from researchers in the field of psychology and neuroscience (Swaminathan and Schellenberg, 2018 ). While most of the researchers have expressed optimism about the benefits of music on cognition (Schellenberg, 2004 ; Slater et al., 2015 ; Tierney et al., 2015 ; Jaschke et al., 2018 ; Nan et al., 2018 ; Barbaroux et al., 2019 ), treatment of psychiatric disorders (Ho et al., 2003 ; Degé and Schwarzer, 2011 ; Chacón-Moscoso et al., 2016 ; Fang et al., 2017 ) as well as on people's overall wellbeing (Hsu and Lai, 2004 ), others have found this enthusiasm unjustified (Sala and Gobet, 2020 ), trying to explain and delineate some research quality failures that arise in the neuroplasticity and music field.

More specifically, in regards to the optimistic point of view, music-based intervention approaches, and practices favor research designs in this domain in relation to implementation and utilitarianism (Reybrouck and Eerola, 2017 ). That is, music can be experienced without necessitating a dedicated sensory organ, the ears, which are its main perceptual apparatus, and after vibrations through the peripheral nervous system, epithelium, and bones induce neuroplastic changes in the human brain. An example of this conclusion is that fetuses and deaf individuals can perceive and respond to music (Chorna et al., 2019 ). Likewise, the infants respond to the rhythmic dimensions of their mothers' speech and emotional tone because of humans' innate ability to engage with the “communicative musicality” of conversation (Lin et al., 2011 ). Also, researchers have found evidence of far-transfer effects related to “therapeutic” traits, or biological and cognitive paths of development (Miendlarzewska and Trost, 2013 ; Carter and Panisch, 2020 ). Typically, this means that a wide range of complex cognitive, emotional, behavioral, and psychophysiological responses can be adjusted through music and, as a result, the mental health of patients with various psychiatric disorders can be improved (Lin et al., 2011 ; Clift, 2012 ; Gustavson et al., 2021 ). Indeed, Gustavson et al. ( 2021 ) have claimed that therapies with active music participation, and structured and multiple sessions have significant positive effects on mood disorders (e.g., depression). Furthermore, Sanfilippo et al. ( 2021 ) have supported that passive music listening reduces anxiety and pain during labor, anxiety symptoms during pregnancy, and postnatal depression.

On the contrary, evidence of systematic reviews or meta-analyses has shown a pessimistic point of view, as described by few, concerning the music's usage and possible direct link to neuroplasticity. According to this literature, there is limited understanding and no clear evidence of how music, directly and indirectly, contributes to mental health (Lin et al., 2011 ; Gustavson et al., 2021 ). Also, the potential causational role of music in cognitive or academic development is very weak (Schellenberg, 2020 ) and conclusions of causation are precluded (Swaminathan and Schellenberg, 2018 ). Therefore, music does not reliably ameliorate psychiatric disorders (Lin et al., 2011 ) and enhance cognitive or academic skills, and there are non-pragmatic neuroplastic changes due to the inability to be reported as a causational link between music and neuroplastic development (Schellenberg, 2020 , p. 430). As a result, positive correlational findings are probably due to confounding (e.g., individual differences) or unidentified variables (i.e., genetic, or demographic factors) that contribute to the confounding ones (Schellenberg, 2020 , p. 431). Besides, far transfer effects of music on development and mental health appear to be an extremely rare occurrence, an over-optimistic and incorrect view, as they stem from a misinterpretation of the empirical data and possibly confirmation bias (Sala and Gobet, 2020 ). For example, Swaminathan et al. ( 2017 ) showed that the correlation between fluid intelligence and engagement in music in a sample of adults was mediated by innate personality factors (i.e., music aptitude) and not trained music skills. Based on this finding, the hypothesis that music training boosts cognition or academic skills cannot be supported. In another example of reviews investigating the effect of listening to music on anxiety symptoms during pregnancy, Sanfilippo et al. ( 2021 ) have argued that the positive correlational effect comes from the predominant use of self-reported measures and, as a consequence, it is not evident the exact mechanism through which music achieves the reduction of pregnant women's anxiety symptoms.

Moreover, the results of far transfer studies seem to be inconclusive or contradictory, due to non-specific or occasional methods used, absence of proper and structured classification of far transfer, lack of a structured understanding of music and musicality, as well as differences in neural activation during the processing of the tasks (Jaschke et al., 2013 ; Fang et al., 2017 ). An example that depicts the lack of uniformity in the test methods used is when comparing two different results of far transfer studies: on the one hand, Ho et al. ( 2003 ) did not show a positive transfer effect of music on visual memory, but on the other hand, Schellenberg ( 2004 ) did show a positive effect of music on intelligence using two different and non-specific IQ measures (Raven's standard matrices and general intelligence). Although both studies analyzed intelligence, Schellenberg ( 2004 ) may have a stronger effect sensitivity because of the generalized measures used. Also, as far as the contrasting far transfer results, some researchers claim that musicians may be at higher risk for mental health problems (Wesseldijk et al., 2019 ), but others suggest the opposite (Teorell et al., 2014 ; Johnson et al., 2017 ). As a result, there are no strong generalizations from their findings because of the variability in outcome measures and music intervention used from one study to another (Lin et al., 2011 ). In the same vein, immature field implementation of methods used and many times non-replicable findings are present in studies investigating the effect of music therapy on Alzheimer's Disease (AD) (Fang et al., 2017 ). For that reason, Fang et al. ( 2017 ) have argued that there are not as many clinical trials as possible with cohort, randomized, blinded, and rigorous methodological investigations for music's therapeutic effect on the topic of AD.

Additionally, meta-analyses that examined the causal link between musical and non-musical abilities reported skeptical results as this link is not clear-cut or, in the case of correlational studies, these associations are not always evident (Swaminathan and Schellenberg, 2018 ). Indeed, there are studies that their findings are more liable to yield a positive effect of music on cognition because the researchers adopt non-standard pedagogies (e.g., training in music-listening skills rather than teaching participants to sing or play an instrument) (Swaminathan and Schellenberg, 2018 ) (for example please see Degé and Schwarzer, 2011 ). Apart from that, firm conclusions referring to the protective effect of music on various psychiatric conditions are difficult to be drawn due to the mixed quality regulation shown in many studies (i.e., small sample sizes, lack of appropriate control groups, few interventions with multiple sessions, omitted necessary information such as inclusion/exclusion criteria regarding the intervention, lack of masking of interviewers during post-test, and randomization concealment) (Wesseldijk et al., 2019 ). As a result, it seems that some researchers cannot clarify how music leads to greater people's health and wellbeing (Gustavson et al., 2021 ).

Discussing the ways forward

Many different neuroscientific and clinical studies have proven that music possesses a beneficial role in cognitive, behavioral, and emotional development (Miendlarzewska and Trost, 2013 ; Carter and Panisch, 2020 ), improving also the overall psychophysiological health of patients with various psychiatric disorders (Lin et al., 2011 ; Gustavson et al., 2021 ; Sanfilippo et al., 2021 ). Nonetheless, according to the aforementioned systematic reviews or meta-analyses (please see above for more details), various factors contribute to a blurred outcome due to non-unified research methods, inconsistent results, misinterpretation or distortion of empirical data, and low reproducibility and replicability of scientific findings, to name just a few. Whilst not all of these factors are necessarily problematic, we believe there is “room” for improvement and development in this research field. For this reason, we propose some state-of-the-art approaches to minimizing the frequency of commonly observed limitations, based on potential solutions that are observed to be universal in empirical research (Lin et al., 2011 ; Boutron and Ravaud, 2018 ; Brown et al., 2018 ; Jaschke et al., 2018 ; Sala and Gobet, 2020 ; Gustavson et al., 2021 ; Ganley et al., 2022 ), and likewise can be applied to this specific domain, too.

More specifically, as far as the limitation of non-unified research methods and heterogeneous results, research should perhaps be conducted through more longitudinal randomized controlled trials (RCTs) combined with both clinical and neuroscientific outcome measures, uniform methodological investigations (e.g., different kinds of control groups) and analysis of sub-groups of tasks proposed (Lin et al., 2011 ; Fang et al., 2017 ; Jaschke et al., 2018 ). Following this perspective, more reliable, accurate, and powerful results, and a consistent research protocol on far transfer from music to cognition/mental health studies can be produced. Besides, the interconnection between music, cognition, and mental health will be better disentangled, perhaps implementing new strategies for music therapy (Lin et al., 2011 ).

As far as the restriction of the results' ineffectiveness is concerned, some researchers suggest that a near transfer effect between music and personal development (e.g., self-esteem) could much easier be successful as it focuses on more technical and visible concepts (i.e., self-esteem) rather than far transfer one that represents a broader and less visible concept among music and cognitive development (e.g., music and cognitive development in mathematics) (Sala and Gobet, 2020 ). On the contrary, more demanding experimental intervention studies should be propitious on the limitations' resolution. That is, the use of larger samples, and improved reporting standards, combined with not only psychological, physiological, and neurochemical aspects, but also with genetic and environmental designs (e.g., longitudinal twin and family studies, for more details please see Purcell, 2002 ), neuroimaging methods (focusing on the reward's circuitry activation, and dynamic patterns of brain activity in health and disease due to music), and biobanks of electronic health record (EHRs) databases estimating music-mental health and other related health associations in large samples (Gustavson et al., 2021 ). As a consequence, the exact interactive mechanism across music and existing risk factors supporting mental health and overall wellbeing can be more easily explored by employing the above approaches.

Moreover, regarding the problem of data misinterpretation or distortion, we can suggest five different and essential solutions to resolve this limitation. Firstly, important information on the full experiment protocol, statistical analysis plan, or sequence of analytical choices and raw data for all designed research should be accessible, reducing the risk of confirmation bias (Boutron and Ravaud, 2018 ). Secondly, maximization of the effect-to-bias ratio in research through random group assignment, incorporation of blinding, and heterogeneity (if possible) into the design should be accomplished to enhance generalizability (Boutron and Ravaud, 2018 ). Thirdly, editors' journals should provide recommendations on how results should be interpreted (e.g., guidelines for the proper use and interpretation of statistical tools), how the conclusions should be reported, and how to avoid misrepresentation of data (Boutron and Ravaud, 2018 ). Fourth, researchers should not only raise evidence for systematic reviews or meta-analyses but also evaluate the quality of the papers themselves following standardized scoring systems (e.g., the “QualSyst” tool developed by Kmet et al., 2004 ) specialized for this kind of inquiry (Chacón-Moscoso et al., 2016 ). Lastly, additional training and tools for peer-reviewers and editors should be included in identifying misrepresentation in clinical research reports and outcome measures (Boutron and Ravaud, 2018 ).

Finally, in relation to the low reproducibility and replicability of scientific findings, in one way, universities should increase awareness of problems in research quality and teach their solutions by adding additional courses (e.g., courses on study design or statistical analysis) (Brown et al., 2018 ). In another way, proper funding and personnel for more pilot and feasibility studies should be important, minimizing many small, non-randomized studies with cross-sectional survey data, and a variety of non-validated questionnaires (Brown et al., 2018 ). Also, partnerships across researchers in academia and research organizations outside of academia (e.g., music industries) or private companies should result in the reassurance of data integrity and results in quality generated in this domain (Ganley et al., 2022 ).

Due to the implementation of non-unified and blurred quality methodological standards, more justification and work are needed to explain music's possible causal link to neuroplasticity. Support of future studies may be apprehended through comparable and inter-connected related outcomes, allowing the presentation of new knowledge content and processes. Therefore, given the variability in published results in the specific field and the difficulty of interpreting these results, the development of stronger, more thorough, and more uniform research methods in quality is urgent (Jaschke et al., 2013 ) as has already been stated in the past (Chacón-Moscoso et al., 2016 ). Solutions mentioned previously such as RCTs, larger sample size, the 5 methods of overcoming data bias and error, and more extensive incorporation of study-validity and feasibility assessment would be our suggested manner of approaching such objectives. Thus, future studies of far transfer from music to mental health and cognitive development could be more reliable and accurate (Jaschke et al., 2013 ). However, these solutions should not be considered a panacea, as science will certainly continue to evolve in the future. Instead, they should be approached as “food-for-thought” for researchers, publishers, regulators, and stakeholders (e.g., funding agencies) to move forward.

Author contributions

EPa and MA: conceptualization. EPa: methodology and supervision. MA and EPi: validation and resources. MA, EPi, and EPa: writing—original draft preparation and writing—review and editing. MA: project administration. All authors have read and agreed to the published version of the manuscript.

The article publication charge for this work was funded by Oslo Metropolitan University.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

  • Allen E. J., Burton P. C., Olman C. A., Oxenham A. J. (2017). Representations of pitch and timbre variation in human auditory cortex . J. Neurosci. 37 , 1284–1293. 10.1523/JNEUROSCI.2336-16.2016 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Arrasmith K. (2020). Infant music development and music experiences: a literature review . Appl. Res. Music Educ. 38 , 9–17. 10.1177/8755123319889669 [ CrossRef ] [ Google Scholar ]
  • Barbaroux M., Dittinger E., Besson M. (2019). Music training with Démos program positively influences cognitive functions in children from low socio-economic backgrounds . PLoS ONE 14 , e0216874. 10.1371/journal.pone.0216874 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Bashwiner D., Bacon D. (2019). Musical creativity and the motor system . Curr. Opin. Behav. Sci. 27 , 146–153. 10.1016/j.cobeha.2018.12.005 [ CrossRef ] [ Google Scholar ]
  • Bespalov A., Steckler T. (2018). Lacking quality in research: Is behavioral neuroscience affected more than other areas of biomedical sciences? J. Neurosci. 300 , 4–9. 10.1016/j.jneumeth.2017.10.018 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Boutron I., Ravaud P. (2018). Misrepresentation and distortion of research in biomedical literature . Proc. Natl. Acad. Sci. U. S. A. 115 , 2613–2619. 10.1073/pnas.1710755115 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brattico E., Tervaniemi M., Näätänen R., Peretz I. (2006). Musical scale properties are automatically processed in the human auditory cortex . Brain Res. 1117 , 162–174. 10.1016/j.brainres.2006.08.023 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Brocke J. V., Liang T. P. (2014). Guidelines for neuroscience studies in information systems research . J. Manag. Inf. Syst. 30 , 211–234. 10.2753/MIS0742-1222300408 [ CrossRef ] [ Google Scholar ]
  • Brown A. W., Kaiser K. A., Allison D. B. (2018). Issues with data and analyses: errors, underlying themes, and potential solutions . Proc. Natl. Acad. Sci. U. S. A . 115 , 2563–2570. 10.1073/pnas.1708279115 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Carter T. E., Panisch L. S. (2020). A systematic review of music therapy for psychosocial outcomes of substance use clients . Int. J. Ment. Health Addict. 19 , 1–8. 10.1007/s11469-020-00246-8 [ CrossRef ] [ Google Scholar ]
  • Chacon-Castano J., Rathbone D. R., Hoffman R., Yang H., Pantazis D., Yang J., et al.. (2017). “Music and the brain-design of an MEG compatible piano,” in 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) . (Jeju Island: IEEE; ), 521–524. [ PubMed ] [ Google Scholar ]
  • Chacón-Moscoso S., Sanduvete-Chaves S., Sánchez-Martín M. (2016). The development of a checklist to enhance methodological quality in intervention programs . Front. Psychol. 7 , 1811. 10.3389/fpsyg.2016.01811 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Chorna O., Filippa M., Sa De Almeida J., Lordier L., Monaci M. G., Hüppi P., et al.. (2019). Neuroprocessing mechanisms of music during fetal and neonatal development: a role in neuroplasticity and neurodevelopment . Neural Plast. 5 , 1–9. 10.1155/2019/3972918 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Clift S. (2012). “Singing, wellbeing, and health,” in Music, Health, and Wellbeing , eds Macdonald, R. A. R., Kreutz, G., and Mitchell, L. A. (Oxford: Oxford University Press; ), 113–124. [ Google Scholar ]
  • Cross K., Fujioka T. (2019). Auditory rhyme processing in expert freestyle rap lyricists and novices: an ERP study . Neuropsychologia 129 , 223–235. 10.1016/j.neuropsychologia.2019.03.022 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Degé F., Schwarzer G. (2011). The effect of a music program on phonological awareness in preschoolers . Front. Psychol. 2 , 124. 10.3389/fpsyg.2011.00124 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Donnay G. F., Rankin S. K., Lopez-Gonzalez M., Jiradejvong P., Limb C. J. (2014). Neural substrates of interactive musical improvisation: an FMRI study of ‘trading fours' in jazz . PLoS ONE 9 , e88665. 10.1371/journal.pone.0088665 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Fang R., Ye S., Huangfu J., Calimag D. P. (2017). Music therapy is a potential intervention for cognition of Alzheimer's Disease: a mini-review . Transl. Neurodegener. 6 , 1–8. 10.1186/s40035-017-0073-9 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Furukawa Y., Uehara K., Furuya S. (2017). Expertise-dependent motor somatotopy of music perception . Neurosci. Lett. 22, 650 , 97–102. 10.1016/j.neulet.2017.04.033 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Ganley E., Coriat A. M., Shenow S., Prosser D. (2022). Systemic problems require systemic solutions: the need for coordination and cooperation to improve research quality . BMC Res. Notes 15 , 51. 10.1186/s13104-022-05932-5 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Gustavson D. E., Coleman P. L., Iversen J. R., Maes H. H., Gordon R. L., Lens M. D. (2021). Mental health and music engagement: review, framework, and guidelines for future studies . Transl. Psychiatry 11 , 1–13. 10.1038/s41398-021-01483-8 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Ho Y. C., Cheung M. C., Chan A. S. (2003). Music training improves verbal but not visual memory: cross-sectional and longitudinal explorations in children . Neuropsychology 17 , 439–450. 10.1037/0894-4105.17.3.439 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Hsu W. C., Lai H. L. (2004). Effects of music on major depression in psychiatric inpatients . Arch. Psychiatr. Nurs. 18 , 193–199. 10.1016/j.apnu.2004.07.007 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Jaschke A. C., Eggermont L. H., Honing H., Scherder E. J. (2013). Music education and its effect on intellectual abilities in children: a systematic review . Rev. Neurosci. 24 , 665–675. 10.1515/revneuro-2013-0023 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Jaschke A. C., Honing H., Scherder E. J. A. (2018). Longitudinal analysis of music education on executive functions in primary school children . Front. Neurosci. 12 , 103. 10.3389/fnins.2018.00103 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Johnson J. K., Louhivuori J., Siljander E. (2017). Comparison of well-being of older adult choir singers and the general population in Finland: a case-control study . Music Sci. 21 , 178–194. 10.1177/1029864916644486 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Kmet L. M., Lee R. C., Cook L. S. (2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields . HTA Initiative 13 , 1–31. Available online at: https://era.library.ualberta.ca/items/48b9b989-c221-4df6-9e35-af782082280e/view/a1cffdde-243e-41c3-be98-885f6d4dcb29/standard_quality_assessment_criteria_for_evaluating_primary_research_papers_from_a_variety_of_fields.pdf [ Google Scholar ]
  • Koelsch S. (2018). Investigating the neural encoding of emotion with music . Neuron 98 , 1075–1079. 10.1016/j.neuron.2018.04.029 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Lin S. T., Yang P., Lai C. Y., Su Y. Y., Yeh Y. C., Huang M. F., et al.. (2011). Mental health implications of music: insight from neuroscientific and clinical studies . Harv. Rev. Psychiatry 19 , 34–46. 10.3109/10673229.2011.549769 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Lin Y. P., Wang C. H., Jung T. P., Wu T. L., Jeng S. K., Duann J. R., et al.. (2010). EEG-based emotion recognition in music listening . IEEE Trans. Biomed. Eng. 57 , 1798–1806. 10.1109/TBME.2010.2048568 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Medina D., Barraza P. (2019). Efficiency of attentional networks in musicians and non-musicians . Heliyon 5 , 1–17. 10.1016/j.heliyon.2019.e01315 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Miendlarzewska E. A., Trost W. J. (2013). How musical training affects cognitive development: rhythm, reward and other modulating variables . Front. Neurosci . 7 , 279. 10.3389/fnins.2013.00279 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Moore E., Schaefer R. S., Bastin M. E., Roberts N., Overy K. (2014). Can musical training influence brain connectivity? Evidence from diffusion tensor MRI . Brain Sci. 4 , 405–427. 10.3390/brainsci4020405 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Nan Y., Liu L., Geiser E., Shu H., Gong C. C., Dong Q., et al.. (2018). Piano training enhances the neural processing of pitch and improves speech perception in Mandarin-speaking children . PNAS 115 , 6630–6639. 10.1073/pnas.1808412115 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Papatzikis E., Elhalik M., Inocencio S. A. M., Agapaki M., Selvan R. N., Muhammed F. S., et al.. (2021). Key challenges and future directions when running auditory brainstem response (ABR) research protocols with newborns: a music and language EEG feasibility study . Brain Sci. 11 , 1–16. 10.3390/brainsci11121562 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Papatzikis E., Papatziki S. (2016). Investigating heart rate and rhythm changes in an infant's music education course: a case study . Psychol. Music 44 , 587–606. 10.1177/0305735615584980 [ CrossRef ] [ Google Scholar ]
  • Papatzikis E., Rishoni H. (2022). “What is music for neuroplasticity? Combined value on infant development and inclusion,” in Rethinking Inclusion and Transformation in Special Education , eds Efstratopoulou, M. (IGI Global; ). 10.4018/978-1-6684-4680-5.ch010 [ CrossRef ] [ Google Scholar ]
  • Papatzikis E., Svec C., Tsakmakidou N. (2019). “Studying neural correlates of music features in the early years education and development process: a preliminary understanding based on a taxonomical classification and logistic regression analysis,” in Proceedings of the Conference: 4th International Conference on Educational Neuroscience, Abu Dhabi, United Arab Emirates, Frontiers in Human Neuroscience . 10–11. [ Google Scholar ]
  • Paus T. (2010). Population Neuroscience: why and How . Hum. Brain Mapp. 31 , 891–903. 10.1002/hbm.21069 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Peretz I. (2006). The nature of music from a biological perspective . Cognition 100 , 1–32. 10.1016/j.cognition.2005.11.004 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Purcell S. (2002). Variance components models for gene-environment interaction in twin analysis . Twin Res. 5 , 554–571. 10.1375/136905202762342026 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Reybrouck M., Eerola T. (2017). Music and its inductive power: a psychobiological and evolutionary approach to musical emotions . Front. Psychol. 8 , 494. 10.3389/fpsyg.2017.00494 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Sala G., Gobet F. (2020). Cognitive and academic benefits of music training with children: a multilevel meta-analysis . Mem. Cogn. 48 , 1429–1441. 10.3758/s13421-020-01060-2 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Sanfilippo K. R. M., Stewart L., Glover V. (2021). How music may support perinatal mental health: an overview . Arch. Womens Ment. Health 24 , 831–839. 10.1007/s00737-021-01178-5 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Savage P. E. (2019). Cultural evolution of music . Palgrave Commun. 5 , 1–12. 10.1057/s41599-019-0221-1 [ CrossRef ] [ Google Scholar ]
  • Savage P. E., Loui P., Tarr B., Schachner A., Glowacki L., Mithen S., et al.. (2020). Music as a coevolved system for social bonding . Behav. Brain Sci. 44 , 1469–1825. 10.31234/osf.io/qp3st [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Schellenberg E. G. (2004). Music lessons enhance IQ . Psychol. Sci. 15 , 511–514. 10.1111/j.0956-7976.2004.00711.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Schellenberg E. G. (2020). “Music training, individual differences, and plasticity,” in Educational Neuroscience, 1st ed , (Routledge; ), 415–441. [ Google Scholar ]
  • Slater J., Skoe E., Strait D. L., O'Connell S., Thompson E., Kraus N. (2015). Music training improves speech-in-noise perception: longitudinal evidence from a community-based music program . Behav. Brain Res. 291 , 244–252. 10.1016/j.bbr.2015.05.026 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Sluming V., Barrick T., Howard M., Cezayirli E., Mayes A., Roberts N. (2002). Voxel-based morphometry reveals increased gray matter density in Broca's area in male symphony orchestra musicians . Neuroimage 17 , 1613–1622. 10.1006/nimg.2002.1288 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Swaminathan S., Schellenberg E. G. (2018). “Music training and cognitive abilities: associations, causes, and consequences,” in The Oxford Handbook of Music and Neuroscience , eds Michael, H. T., and Donald, A. H., (Oxford University Press; ), 645–661. 10.1093/oxfordhb/9780198804123.013.26 [ CrossRef ] [ Google Scholar ]
  • Swaminathan S., Schellenberg E. G., Khalil S. (2017). Revisiting the association between music lessons and intelligence: training effects or music aptitude? Intelligence 62 , 119–124. 10.1016/j.intell.2017.03.005 [ CrossRef ] [ Google Scholar ]
  • Talwar N., Crawford M. J., Maratos A., Nur U., McDermott O., Procter S. (2006). Music therapy for in-patients with schizophrenia: exploratory randomised controlled trial . Br. J. Psychiatry 189 , 405–409. 10.1192/bjp.bp.105.015073 [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Teorell T., Lennartsson A. K., Mosing M. A., Ullen F. (2014). Musical activity and emotional competence - a twin study . Front. Psychol. 5 , 774. 10.3389/fpsyg.2014.00774 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Tierney A. T., Krizman J., Kraus N. (2015). Music training alters the course of adolescent auditory development . PNAS 112 , 10062–10067. 10.1073/pnas.1505114112 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Van de Winckel A., Feys H., De Weerdt W., Dom R. (2004). Cognitive and behavioural effects of music-based exercises in patients with dementia . Clin. Rehabil. 18 , 253–260. 10.1191/0269215504cr750oa [ PubMed ] [ CrossRef ] [ Google Scholar ]
  • Wesseldijk L. W., Ullén F., Mosing M. A. (2019). The effects of playing music on mental health outcomes . Sci. Rep. 9 , 12606. 10.1038/s41598-019-49099-9 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

  • Machine learning
  • Social justice
  • Black holes
  • Classes and programs


  • Aeronautics and Astronautics
  • Brain and Cognitive Sciences
  • Architecture
  • Political Science
  • Mechanical Engineering

Centers, Labs, & Programs

  • Abdul Latif Jameel Poverty Action Lab (J-PAL)
  • Picower Institute for Learning and Memory
  • Lincoln Laboratory
  • School of Architecture + Planning
  • School of Engineering
  • School of Humanities, Arts, and Social Sciences
  • Sloan School of Management
  • School of Science
  • MIT Schwarzman College of Computing

Exposure to different kinds of music influences how the brain interprets rhythm

Press contact :, media download.

Illustration of five diverse people wearing headphones or earphones. A curvy staff line with treble chef and notes are in background

*Terms of Use:

Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license . You may not alter the images provided, other than to crop them to size. A credit line must be used when reproducing images; if one is not provided below, credit the images to "MIT."

Illustration of five diverse people wearing headphones or earphones. A curvy staff line with treble chef and notes are in background

Previous image Next image

When listening to music, the human brain appears to be biased toward hearing and producing rhythms composed of simple integer ratios — for example, a series of four beats separated by equal time intervals (forming a 1:1:1 ratio).

However, the favored ratios can vary greatly between different societies, according to a large-scale study led by researchers at MIT and the Max Planck Institute for Empirical Aesthetics and carried out in 15 countries. The study included 39 groups of participants, many of whom came from societies whose traditional music contains distinctive patterns of rhythm not found in Western music.

“Our study provides the clearest evidence yet for some degree of universality in music perception and cognition, in the sense that every single group of participants that was tested exhibits biases for integer ratios. It also provides a glimpse of the variation that can occur across cultures, which can be quite substantial,” says Nori Jacoby, the study’s lead author and a former MIT postdoc, who is now a research group leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt, Germany.

The brain’s bias toward simple integer ratios may have evolved as a natural error-correction system that makes it easier to maintain a consistent body of music, which human societies often use to transmit information.

“When people produce music, they often make small mistakes. Our results are consistent with the idea that our mental representation is somewhat robust to those mistakes, but it is robust in a way that pushes us toward our preexisting ideas of the structures that should be found in music,” says Josh McDermott, an associate professor of brain and cognitive sciences at MIT and a member of MIT’s McGovern Institute for Brain Research and Center for Brains, Minds, and Machines.

McDermott is the senior author of the study, which appears today in Nature Human Behaviour. The research team also included scientists from more than two dozen institutions around the world.

A global approach

The new study grew out of a smaller analysis that Jacoby and McDermott published in 2017. In that paper , the researchers compared rhythm perception in groups of listeners from the United States and the Tsimane’, an Indigenous society located in the Bolivian Amazon rainforest.

To measure how people perceive rhythm, the researchers devised a task in which they play a randomly generated series of four beats and then ask the listener to tap back what they heard. The rhythm produced by the listener is then played back to the listener, and they tap it back again. Over several iterations, the tapped sequences became dominated by the listener’s internal biases, also known as priors.

“The initial stimulus pattern is random, but at each iteration the pattern is pushed by the listener’s biases, such that it tends to converge to a particular point in the space of possible rhythms,” McDermott says. “That can give you a picture of what we call the prior, which is the set of internal implicit expectations for rhythms that people have in their heads.”

When the researchers first did this experiment, with American college students as the test subjects, they found that people tended to produce time intervals that are related by simple integer ratios. Furthermore, most of the rhythms they produced, such as those with ratios of 1:1:2 and 2:3:3, are commonly found in Western music.

The researchers then went to Bolivia and asked members of the Tsimane’ society to perform the same task. They found that Tsimane’ also produced rhythms with simple integer ratios, but their preferred ratios were different and appeared to be consistent with those that have been documented in the few existing records of Tsimane’ music.

“At that point, it provided some evidence that there might be very widespread tendencies to favor these small integer ratios, and that there might be some degree of cross-cultural variation. But because we had just looked at this one other culture, it really wasn’t clear how this was going to look at a broader scale,” Jacoby says.

To try to get that broader picture, the MIT team began seeking collaborators around the world who could help them gather data on a more diverse set of populations. They ended up studying listeners from 39 groups, representing 15 countries on five continents — North America, South America, Europe, Africa, and Asia.

“This is really the first study of its kind in the sense that we did the same experiment in all these different places, with people who are on the ground in those locations,” McDermott says. “That hasn’t really been done before at anything close to this scale, and it gave us an opportunity to see the degree of variation that might exist around the world.”

Cultural comparisons

Just as they had in their original 2017 study, the researchers found that in every group they tested, people tended to be biased toward simple integer ratios of rhythm. However, not every group showed the same biases. People from North America and Western Europe, who have likely been exposed to the same kinds of music, were more likely to generate rhythms with the same ratios. However, many groups, for example those in Turkey, Mali, Bulgaria, and Botswana showed a bias for other rhythms.

“There are certain cultures where there are particular rhythms that are prominent in their music, and those end up showing up in the mental representation of rhythm,” Jacoby says.

The researchers believe their findings reveal a mechanism that the brain uses to aid in the perception and production of music.

“When you hear somebody playing something and they have errors in their performance, you’re going to mentally correct for those by mapping them onto where you implicitly think they ought to be,” McDermott says. “If you didn’t have something like this, and you just faithfully represented what you heard, these errors might propagate and make it much harder to maintain a musical system.”

Among the groups that they studied, the researchers took care to include not only college students, who are easy to study in large numbers, but also people living in traditional societies, who are more difficult to reach. Participants from those more traditional groups showed significant differences from college students living in the same countries, and from people who live in those countries but performed the test online.

“What’s very clear from the paper is that if you just look at the results from undergraduate students around the world, you vastly underestimate the diversity that you see otherwise,” Jacoby says. “And the same was true of experiments where we tested groups of people online in Brazil and India, because you’re dealing with people who have internet access and presumably have more exposure to Western music.”

The researchers now hope to run additional studies of different aspects of music perception, taking this global approach.

“If you’re just testing college students around the world or people online, things look a lot more homogenous. I think it’s very important for the field to realize that you actually need to go out into communities and run experiments there, as opposed to taking the low-hanging fruit of running studies with people in a university or on the internet,” McDermott says.

The research was funded by the James S. McDonnell Foundation, the Canadian National Science and Engineering Research Council, the South African National Research Foundation, the United States National Science Foundation, the Chilean National Research and Development Agency, the Austrian Academy of Sciences, the Japan Society for the Promotion of Science, the Keio Global Research Institute, the United Kingdom Arts and Humanities Research Council, the Swedish Research Council, and the John Fell Fund.

Share this news article on:

Related links.

  • Josh McDermott
  • Department of Brain and Cognitive Sciences
  • McGovern Institute

Related Topics

  • Brain and cognitive sciences
  • Center for Brains Minds and Machines
  • National Science Foundation (NSF)

Related Articles

Through research trips to the remote Bolivian rainforest, researchers in the McDermott lab at the McGovern Institute for Brain Research has found that aspects of the perception of note combinations may be universal.

Universal musical harmony

Eduardo Undurraga, an assistant professor at the Pontifical Catholic University of Chile, runs a musical pitch perception experiment with a member of the Tsimane’ tribe of the Bolivian rainforest.

Perception of musical pitch varies across cultures

A team of neuroscientists has found that people are biased toward hearing and producing rhythms composed of simple integer ratios — for example, a series of four beats separated by equal time intervals.

How the brain perceives rhythm

Brandeis University professor Ricardo Godoy conducts the experiment in a village in the Bolivian rainforest. The participants were asked to rate the pleasantness of various sounds, and Godoy recorded their response.

Why we like the music we do

Previous item Next item

More MIT News

A blue-tinted human eye has a robotic-like overlay. The edges of the image have yellow circles showing scenes like people smiling, flowers, and a truck. These circles get blurrier the further away from the eyeball they are.

Researchers enhance peripheral vision in AI models

Read full story →

A coronal cross-section of a mouse brain is stained blue. The entire outer edge and occasional points further inside are speckled with yellow-green dots.

How sensory gamma rhythm stimulation clears amyloid in Alzheimer’s mice

Close-up of a dress neckline on a mannequin being targeted by a laser

Is this the future of fashion?

12 astronauts in blue jumpsuits appear on stage. Several are clapping or waving at the crowd.

Three MIT alumni graduate from NASA astronaut training

Illustration shows a pink woman breathing in, and a blue woman singing. Pink arrows point toward them, and blue arrows point away.

How the brain coordinates speaking and breathing

Multiple robotic arms working in close proximity inside a warehouse setting

Method rapidly verifies that a robot will avoid collisions

  • More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

  • Map (opens in new window)
  • Events (opens in new window)
  • People (opens in new window)
  • Careers (opens in new window)
  • Accessibility
  • Social Media Hub
  • MIT on Facebook
  • MIT on YouTube
  • MIT on Instagram


  1. Research Papers about Music: Writing Process Features

    youtube music research paper

  2. History of Jazz Music Research Paper.docx

    youtube music research paper


    youtube music research paper

  4. Music and Studying (600 Words)

    youtube music research paper

  5. Musical Composer Research Paper by Stephanie Gust

    youtube music research paper

  6. Music Research Paper Topics You Might Consider Using

    youtube music research paper


  1. Top 25 Outstanding Music Research Topics for Students of 2023

  2. Music books and writers

  3. 12th Music Instrument 035 (set-4)| CBSE Question-Paper Solution 2023-24

  4. Thesis

  5. music for writing papers

  6. Timelapse Writing of a Research Paper


  1. Music on YouTube: User engagement with traditional, user-appropriated and derivative videos

    The contributions of this paper are three-fold. First, given the constant change of digital music consumption, we provide a historical snapshot of music interaction with recorded music on YouTube in 2013-2014. This reveals the importance of music among YouTube's content categories.

  2. Listening to music videos on YouTube. Digital consumption practices and

    We describe three types of online music practices according to the role YouTube plays in, that correlate with music passion: YouTube can be framed as a free and open listening platform (especially to casual listeners), as an efficient soundtracking device in many contexts, as a useful complementary listening and music sharing device. The paper ...

  3. Follow the algorithm: An exploratory investigation of music on YouTube

    This article offers a contribution to the fields of popular music studies, cultural and media sociology by presenting an exploratory study of the network of associations among 22,141 YouTube music videos, as produced by the platform recommender algorithm ( Celma, 2010 ). The aims of this study are to: a) reconstruct how musical content clusters ...

  4. Exploring Music Video Experiences and Their Influence on Music

    Music videos (MVs) offer a unique musical experience that allows listeners to engage with songs in an audio-visual format. Research has shown that pairing music with visuals can have a significant influence on the perception of the music's meaning and affective quality (Boltz, 2004; Boltz et al., 2009; Cohen, 2001).However, this research has focused almost exclusively on music in the context ...

  5. "Music Has No Borders": An Exploratory Study of ...

    Thematic analysis was used to code and organize data, providing a methodological flexibility suitable for an exploratory study (Braun and Clarke, 2006).The research is underpinned by a pragmatic philosophy that considers knowledge to be influenced by social experiences, and simultaneously constructed and real (Biesta, 2015).YouTube pages were imported as PDFs into NVivo 12 for Mac (QSR ...

  6. Fifteen years of YouTube scholarly research: knowledge ...

    The analysis revealed that 2006-2007 were initial stage in YouTube research followed by 2008 -2017 which is the decade of rapid growth in YouTube research. The 2017 -2021 is considered the stage of consolidation and stabilization of this research topic. ... Analyzing research trends in YouTube papers requires the use of the bibliometric method.

  7. Music Videos on YouTube: Exploring Participatory Culture on Social

    Existent research indicates that music videos are one of the most salient features of YouTube. Interactionist research about popular music has provided important insights through interviews with fans and audience members; however, this work has yet to examine audience engagement with music videos on YouTube. Using Qualitative Media Analysis, I ...

  8. Follow the algorithm: An exploratory investigation of music on YouTube

    The research methods used in this paper take inspiration from the 'digital methods' approach (Rogers, 2013), according to which we should 'follow the medium' to study cultural and social phenomena unfolding on the Web. ... The analysis of the network associations within a large sample of YouTube music videos has shown how the users ...

  9. What to watch: Practical considerations and strategies for using

    In this paper, we provide a conceptual schematic by which future research utilizing YouTube data can build from. We also discuss challenges, considerations and recommendations for both quantitative and qualitative researchers seeking to leverage the YouTube platform as both a data collection tool and an open source of data; these discussions are conjointly mapped onto the step-by-step table ...

  10. Music and neuroscience research for mental health, cognition, and

    Developmental neuroscience has studied the processing and perception of music in the fetal and infant brain and its selective role in environmental enrichment and socioemotional development (Papatzikis and Papatziki, 2016; Chorna et al., 2019; Arrasmith, 2020; Papatzikis et al., 2021 ). Mental health research suggests the potential benefits of ...

  11. Exposure to different kinds of music influences how the brain

    When listening to music, the human brain appears to be biased toward hearing and producing rhythms composed of simple integer ratios — for example, a series of four beats separated by equal time intervals (forming a 1:1:1 ratio).

  12. Understanding YouTube Culture and How It Affects Today's Media

    extremely user friendly so everyone has access to it. People just need the drive and the know-how. Christopher Cayari's "The YouTube Effect" (2011) highlights the way. YouTube affects connections to education, technology, and media. YouTube's first facet. of content began with music and music videos.

  13. YouTube Music as an Innovative Teaching Media to Improve Students

    Abstract. This research aims to investigate the effectiveness of YouTube Music platform as teaching media to improve students' listening mastery. It is believed that YouTube Music as an ...

  14. PDF and YouTube Music A Comparative Study of Spotify Audio Streaming

    Methodology. Passive Measurement: Observation of overall network traffic flow from one or more vantage points. Campus level. Capture card from Network edge router. Bro connection logs (timestamps, IP addresses and ports of the source and destination, connection duration, connection state, number. Active Measurement:

  15. PDF Audio Streaming Application Performance: A Comparative Study of Spotify

    The rest of this paper is organised into five additional sections. Section 2 provides background information and ... research fails to compare it with the fastest growing music streaming site, YouTube Music. Because of this, a comparison ... YouTube Music Math Science Laboratories 15:03 2021-09-24 Edu secure MacEwan Hall 11:31 2021-10-05 Eduroam

  16. Music Videos on YouTube: Exploring Participatory Culture on Social

    Abstract The body of scholarship on YouTube is an expanding area of scholarly inquiry. Existent research indicates that music videos are one of the most salient features of YouTube. Interactionist research about popular music has provided important insights through interviews with fans and audience members; however, this work has yet to examine audience engagement with music videos on YouTube.

  17. PDF The impact that music streaming services such as Spotify, Tidal and

    of music streaming services with the wishes of the music industries consumers, artists and record labels. This research paper was researched using the current literature available that has been written on the three music streaming services. The influence of piracy on the music industry will also be analysed.

  18. (PDF) The YouTube video recommendation system

    Abstract and Figures. We discuss the video recommendation system in use at YouTube, the world's most popular online video community. The system recommends personalized sets of videos to users ...

  19. YouTube channels, uploads and views: A statistical analysis of the past

    SUBMIT PAPER. Convergence: The International Journal of Research into New Media Technologies. ... Salovaara A (2015) Music on YouTube: User engagement with traditional, user-appropriated and derivative videos. ... His research examines the potential of social media data in general and the role of educational videos on YouTube. He is the author ...

  20. Music Research Methods 8a: More on Research / Paper Proposals

    A discussion, with an example, of the structure and content of a research / paper proposal.

  21. 7 Benefits of Using Research Paper Music Topics with Your ...

    Are you looking for new and exciting ways to engage your music appreciation students?Music research paper topics are a great way to help students explore spe...

  22. A Content Analysis in the Studies of YouTube in Selected Journals

    This paper provides a review of research trends and content analysis of studies in the field of YouTube that were published in seven major journals: Turkish Online Journal of Educational Technology (TOJET), Educational Technology & Society (ET&S), Educational Technology Research & Development (ETR&D), Computers & Education (C&E), Learning and Instruction (L&I), Australasian Journal of ...

  23. YouTube Music

    YouTube Music is a new music service that lets you enjoy official albums, singles, videos, remixes, live performances and more on your Android, iOS or desktop device. Whether you want to listen to Marllen's Masseve or discover new artists and genres, YouTube Music has it all.

  24. (PDF) Abstractive Summarizer for YouTube Videos

    PDF | On May 1, 2023, Sulochana Devi and others published Abstractive Summarizer for YouTube Videos | Find, read and cite all the research you need on ResearchGate

  25. Plagiarism Detection Software

    Plagiarism Detection Software | Research Aptitude by Aditi Mam | UGCNET Paper-1 & Ph.D 2024 | JRFAdda UGC NET Paper 1 by Aditi Mam Complete Playlist:👉 htt...