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Digital strategies and culture: What you should know and why it matters

What is digital culture?

There’s no question that in today’s professional world, fluency in digital technologies is considered an asset. In fact, worldwide spending on digital transformation—which includes everything from automated work processes to cybersecurity and artificial intelligence—is predicted to hit $3.4 trillion by 2026 . This technological revolution also requires a shift to digital culture and digital strategies in the workplace wherein employees use these digital tools to innovate new products and solutions, collaborate with one another, and deliver targeted offerings that are best suited to customers and clients.

If you’re interested in developing skills as a critical consumer, designer, and creator of content for the internet, social media, or other digital media, explore the Digital Strategies and Culture Certificate at Penn LPS Online. The Ivy League online courses in this program provide flexible approaches for using technology to reach your personal and professional goals. You’ll also learn how to communicate this technological savvy effectively across diverse professional contexts.

Characteristics and benefits of digital culture

Robust digital cultures allow companies to become more efficient, adaptative, and growth-oriented. Read on to explore some additional advantages to developing digital cultures in the workplace.

Enhanced collaboration

One of the major benefits of a strong digital culture is the ability to connect through Zoom, Slack, or Microsoft Teams and better collaborate with team members across locations and time zones. Digital technologies such as Google Hangouts or Dropbox also make for easier partnerships when working on projects, brainstorming ideas, and sharing documents among employees. Implementing a digital collaboration network can also help to enhance workflows, enrich productivity, improve access to pertinent information, and foster greater team interaction and engagement. With greater collaboration, there is a greater likelihood for unique and impactful ideation.

In ORGC 2010: Virtual Collaboration at Penn LPS Online, you’ll explore the relationship between the tools, technologies, and human factors, as well as the cultural and social frameworks necessary to create strong collaboration. Through key concepts, including complexity and interdependence amongst virtual teams, leaders, and organizations, you’ll gain insight into how to navigate, learn, collaborate, and lead in today’s complex digital landscape. You’ll hear from guests who share their experiences and best practices for successful virtual teams and operations.

Greater transparency

To build a strong digital culture, it’s necessary to regularly share meaningful information and feedback across teams and stakeholders. Digital workspaces allow for more transparency and better communication because leaders can access superior tools to openly share knowledge across multiple channels. This improved information flow increases company efficiency and also helps to build a culture of organizational trust. This increased trust can empower employees to share their ideas, improve employee engagement and happiness, boost job performance, and enhance employee retention.

As technology has evolved at a rapid pace since the invention of the microchip in the 1970s, the social, economic, and cultural parameters regarding how we behave with one another and new technologies have been tested. In DIGC 3600: Applications of Digital Culture , you’ll explore the implications and consequences of digital culture and digital literacy through the lens of ethics, privacy, communication, and identity. You’ll work on creating specialized arenas of digital culture with a framework for engaging with technological change in your daily life.

Increased data-driven innovation

A critical advantage of digital workplaces, cultures, and strategies is the ability to collect and analyze data to inform business decision-making. This allows organizations to become more customer-centric as they uncover important patterns, learn from customer feedback, and adjust or design new offerings aligned with target audience preferences. The insights gained through data analytics enable companies to create consumer profiles and use them to develop digital journeys customized to their historical needs and buying behavior. The more data that is gleaned, the easier it will be to come up with relevant concepts and pinpoint market opportunities that are not currently being met.

In DIGC 2200: Design Thinking for Digital Projects , you’ll learn how to empathize with your audience, define the problem, innovate, prototype, and test. As you build your critical thinking and technological understanding, you’ll apply these skills to help you recognize and solve specific digital problems. Through an ethnographic approach to understanding the diverse needs of communities, you’ll look at case studies that will inform your own design thinking project at the end of the course.

Added flexibility

Agility and adaptability are important attributes of virtually every successful organization. Digital technologies and cultures provide companies with the flexibility to respond more quickly and effectively to changing market dynamics, customer needs, or internal issues. When it comes to employees, those well-versed in the use of the latest digital tools will be more adaptable themselves when presented with new challenges, able to use data-driven insights to make decisions, and confident in employing digital tools to come up with unique solutions.

If you’d like to enhance your professional adaptability by learning a new technological skill, then explore DIGC 2000: Coding Foundations for Digital Strategies . In this course, you’ll obtain a basic understanding of program code and structures that are ubiquitous across all programming languages. As you analyze the possibilities and implementations of computer programs and explore strategies for engaging with digital development tools, you’ll also think critically about how programming decisions may impact others. You’ll be introduced to the Scientific Python Development Environment (Spyder), an open-source cross-platform Integrated Development Environment (IDE) used by programmers worldwide. If you find your interest is piqued, you can then enroll in DIGC 3000: Intermediate Coding for Digital Strategies to further your expertise.

The future of digital marketing strategy

With the help of website analytics tools like Google Analytics, organizations gain valuable information on user activity that can be used to develop targeted digital strategies to align with user profiles. When this vast wealth of consumer data is combined with innovations in artificial intelligence (AI) and machine learning, the ability to produce targeted ads that align with buying habits, needs, and interests of consumers is only further enhanced.

This is particularly relevant when it comes to eCommerce stores and brands that can use the data collected to understand what their users are doing online, including social media, to inform strategy and add value. For example, if consumers consistently make a habit of visiting another brand’s digital store after making a purchase, then creating a partnership that offers a combined discount offer is an obvious choice. In 2023, the social media ad spend in the US is expected to be just over $94.4 billion, and it could reach $130.5 billion by 2027.

If you’d like to learn how to use social media campaigns to create engaging messaging, build an organizational or brand identity, and cultivate user loyalty, PROW 4000: Writing for Social Media is an ideal fit. You’ll explore how readers and designers approach multimedia texts by bringing together language, image, sound, and gesture to create coherent messages. By the end of the course, you’ll build a multiplatform portfolio of social media content to illustrate your expertise to your employer or potential clients.

Another rising trend in digital marketing and strategy is voice search. With improvements in AI technology, the use of digital assistants in GPS devices in cars, smartphones, televisions, and speakers has increased greatly in recent years. In 2022, 20% of Google searches on mobile were through voice , 40% of all internet searches in the US were voice-based, and 58% of consumers used voice search to query local business information.

If you’re looking to build skills to help you break into the field of digital marketing and strategy, PROW 4010: Composing a Professional Identity from the Certificate in Digital Strategies and Culture at Penn LPS Online is an ideal choice. In this course, you’ll develop rhetorical fluency with regard to job searches and career advancement, including identifying and researching potential job opportunities, networking, and developing mentor relationships. With peer and professor feedback, you’ll build a professional profile that includes a cover letter, resume, LinkedIn profile, and a web portfolio to showcase your experience and talent.

Learn more about the Digital Strategies and Culture Certificate

Looking to pursue a digital strategy certificate online that was designed to easily integrate into your personal and professional obligations? The 4-course Digital Strategies and Culture Certificate at Penn LPS Online provides the opportunity to develop your digital literacy, explore creating audience-specific digital content, and communicate and collaborate effectively in virtual workspaces. And it is offered on an accelerated 8-week schedule that allows you to continue to advance your career as you enhance your qualifications.

The coursework in this certificate focuses on flexible approaches for using technology to help solve complex problems and interpret and analyze various forms of data. As you build digital platform fluency, you’ll gain skills and strategies for building and maintaining strategic partnerships across dynamic networks and virtual environments. You’ll also discover how to use and read general purpose coding language and design, deliver, and manage engaging content for digital audiences.

Ready to take the first step toward enhancing your digital fluency and boosting your resume? Fill out your application  at Penn LPS Online today and enroll in the Certificate in Digital Strategies and Culture . You can also register for individual classes in the Digital Culture course block without committing to the certificate program. Or browse  our course guide  to see a full range of what’s available in any upcoming term.

Digital Culture & Society

• Submissions
• Editorial Board
• CfP: Digital Material/ism
• CfP: Quantified Selves
• CfP: Making and Hacking
• CfP: Mobile Digital Practices
• CfP: Rethinking AI
• CfP: Digital Citizens
• CfP: Inequalities and Divides
• CfP: Special Issue Proposals
• CfP: Laborious Play
• CfP: DIY Histories
• CfP: The Politics of Metadata
• CfP: Networked Images
• CfP: Taming digital practices
• CfP: Coding Covid-19: The Rise of the App-Society
• CfP: Frictions
• CfP: Ruins and the Contemporary
• 1(1) 2015: Digital Material/ism
• 2(1) 2016: Quantified Selves
• 2(2) 2016: Politics of Big Data
• 3(1) 2017: Making & Hacking
• 3(2) 2017: Mobile Digital Practices
• 4(1) 2018: Rethinking AI
• 5(1) 2019: Inequalities and Divides

About the Journal

Digital Culture & Society is a refereed, international journal, fostering discussion about how digital technologies, platforms and applications reconfigure daily lives and practices. It offers a forum for critical analysis and inquiries into digital media theory. The journal provides a publication environment for interdisciplinary research approaches, contemporary theory developments and methodological innovation in digital media studies. It invites reflection on how culture unfolds through the use of digital technology, and how it conversely influences the development of digital technology itself.

The journal is a research platform for those interested in the interdisciplinary field of digital media studies. Its goal is to create a cross-disciplinary repository on the interconnection between research fields such as media studies, cultural studies, science and technology studies, sociology, gender studies, anthropology, game studies, media/art history and information science. It welcomes contributions addressing the relevance of interventional approaches, such as action research and media archaeology, as well as articles related to material culture studies, actor-network theory, critical code studies and software studies.

Digital Culture & Society seeks contributions that display a clear, inspiring engagement with media theory and/or methodological issues. Emphasising the relevance of new practices and technology appropriation for theory as well as methodology debates, the journal also encourages empirical investigations.

The journal’s structure reflects the editors’ aim to spark and incorporate the discourse on digital media practices, theory, history and methodologies. Each issue consists of 3 sections:

• The main section of each issue is dedicated to an overarching theme which has been specified in the respective call for papers . The editors aim at including a range of articles that involve theoretical and/or methodological debates, preferably in the light of authors’ own empirical investigations.
• “Entering the Field”  presents initial and ongoing empirical work in digital media studies. The editors have created this experimental section to provide a platform for researchers who would like to initiate a discussion concerning their emerging, yet maybe incomplete research material and plans as well as methodological insights.
• “In Conversation with …” presents dialogues between the editors and authors of recently published works in the field of digital media studies. The interviews will be closely related to the respective issue’s main theme.

If you are interested in submitting a paper or would like to contribute to an interview, please take a look at our submission guidelines   and our recent calls for papers .

(Founding) Editors

Pablo Abend , University of Cologne (GER), co-founder and editor 2014-today

Mathias Fuchs , Leuphana University Lüneburg (GER), co-founder and editor 2014-today

Anna Näslund , Department of Culture and Aesthetics, Stockholm University, editor 2023-today

Ramón Reichert , University of Vienna (AT), co-founder and editor 2014-today

Annika Richterich , University of Sussex (UK) and Maastricht University (NL), co-founder and editor 2014-2020

Karin Wenz , Maastricht University (NL), co-founder and editor 2014-today

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Digital Culture: The Driving Force of Digital Transformation

D igital technology and business models are driving business disruption. The pandemic has accelerated this trend, making digital transformation critical for business success. However, it takes more than technology alone; leaders need to look at the human side of their organizations. Culture and the way people interact with technology are significant factors in digital success.

This interactive guide, created in collaboration with business executives and academia, presents actionable frameworks and tools for executives to improve digital leadership and culture in their organizations.

World Economic Forum reports may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License , and in accordance with our Terms of Use .

Essay on Digital Culture, Technologies and Formation of Popular Culture

Introduction

The advancement of technology cross the world has led to increased use of digital technologies within society. It is important to note that digital technology is a pillar towards globalization and development of popular culture (Gawer, 2014). The essay seeks to explore through different theoretical perspectives, the impact of digital culture and technologies on the formulation of popular culture. Popular culture in a community implies to a set of recognizable beliefs, practices and objects that are essential to individuals at a given point. The development and incorporation of technology into culture has had an impact on cultural orientations. There are different theoretical perspectives that can be used to explain the impact of digital technologies on cultural orientations within a country (Deuze, 2006). Examples of theories that can help gain a deeper understanding to the matter includes post-modernism, functionalism, structuralism, feminism and Marxism. An examination on the theories mentioned can help gain a deeper understanding on how culture evolves and develops in society. The development of a culture where people rely on digital technology has changed the scope of cultural operations and growth (Ceron-Anaya, 2010). For instance, changes in the film industry and pop music illustrate that culture has changed and is transforming due to interactions that happen. The essay will focus on highlighting the impact of digital culture and technologies on the formulation of popular culture.

Popular Culture and its Formulation

Popular culture within society is formed when members of the community recognize some practices and beliefs as important. For instance, some meals have specific features and preparation procedures that make them unique and recognizable to particular community (Waldfogel, 2018). Cultural experiences and attitudes in society play an important role in determining the culture that exists within the place. Popular culture can refer to music that a particular society embraces and aspects of technology involved. A base ball game in the United States is n illustration of popular culture that began decades ago in the country. When a community readily agrees on accessible cultural experiences, the new practices and beliefs can be referred to popular culture (Deuze, 2006). Internet activism is on the rise and it is important to explore it is an example of popular culture that has developed with regards to digital culture. Equally, political practices within the United States can illustrate adopting of a popular culture. Popular culture forms when individuals within a place are used to specific practices, beliefs and other issues that impact life in society. The internet era has changed the scope of operations for many aspects in society life (Gawer, 2014). In essence, popular culture develops as a set of practices that a particular community recognizes as important at a particular time. For instance, internet marketing is one popular culture that has emerged due to use of digital technology in business.

Internet Use and Impact on Formulation of Popular Culture

The development of the internet across the world has changed the scope of operations across many divides in the world. The internet affects popular culture across the world in a significant way and it is important for the essay to explore how it impacts the formulation of a culture in various societies (Niemeyer and Keightley, 2020). Culture is designed as shared behavior that affects people within a society in one way or the other. The es6tablishment of information and technologies in the world has boosted globalization in a significant manner. Culture is an essential aspect that can help change the scope of operations in business, education and other sectors of the economy. It is important that the essay applies the postmodernism theory in culture to explain important changes and possible impacts of the use of internet on formulation of a popular culture (Causey, 2007). The internet has been a pillar to the formulation of digital culture that has influenced popular culture to a large extent. For instance, internet activism is on the rise with the establishment of digital technologies. There are many organizations across the world that uses the internet as a platform where they reach out to people from different parts of the world. An example of internet activism that is evident includes political campaigns and health campaigns (Waldfogel, 2018). Equally, black activism is one of the most famous online activism that has happened in the recent past. Black people and other activists in support have been utilizing social media platforms as a way of rallying support.

Feminism is another activist movement that has done well in the recent past due to the development of digital technology. Platforms such as Facebook, Twitter, Instagram, and YouTube have proved instrumental in reaching out to the public and speaking out particular concerns that affect the lives of women in society (Causey, 2007). The digital culture has developed a individuals can communicate online and share their experiences. In essence, the development of the internet has been a boost to the change of the way popular culture is formulated. For instance, using Facebook to share and receive news has been a development that has taken the world by storm. Social media platforms have proved to attract more traffic than offline platform, which makes it easier for people to interact and share. Communication is one of the pillars towards change in society and feminist movements have utilized the opportunity. In most societies, women had no voice in society and had no representations on political platforms (Lee, 2009). However, with increased activism, much has changed to accommodate women in various fields within the economy. In essence, feminism has gained popularity and taken effect across the world as aided by internet activism.

Digital Food Cultures and Popular Culture

The recent developments in digital technology have taken the world by storm including development of a culture where consumers can purchase food online. For instance, individuals can use the internet to order for food from online platforms across the world (Niemeyer and Keightley, 2020). The development of a culture where individuals can remotely and conveniently order for food of their choices is an indication of the establishment of popular culture. There are many e-platforms that sell food products and it is convenient for customers to order. One of the most interesting facts about the development of popular culture is that the society has transformed and incorporated the new ways of operation. Staying healthy is an important aspect that individuals in society monitor (Waldfogel, 2018). The use of internet and social media devices have led to establishment of a culture where people can request for meals from remote locations in a convenient manner. In essence, much has changed due to development of digital food cultures that aim to give the customer a different experience. The conflict theory of cultural transformation can help explain how communities across the world have faced challenges due to cultural differences and beliefs (Ceron-Anaya, 2010). For instance, race is a sensitive factor that has led to social injustices in most parts of the world. The development of a culture where individuals in society are defined by class, race or gender is detrimental towards economic growth and development.

It is important to examine how digital food culture has led to establishment of a popular culture in the world. The conflict theory is a position to account for differences that are notable based on tastes, preferences and choices (Kent, 2020). For instance, people in the middle or high class can purchase food products online since they have internet accessibility. Lack of internet can be detrimental to use of digital technologies to achieve efficiency in an economy. Inequalities in the world have led to development of a culture where people recognize the differences (Strachan, 2017). Some people in society can afford to order for food online unlike those in the lower social class where individuals struggle to make ends meet. Self-tracking is another aspect that has risen due to development of digital technologies. Customers can track hotels and restaurants with healthier food products for their own good. The digital food culture across the world is an illustration of the impact of technology in formulation of a popular culture that is recognized (Tatarchevskiy, 2011). In the recent past, there was no online platform that could sell food and track how well their customers are doing. The advancement of digital technology is an indication that popular culture can develop at any time when society recognizes some beliefs and aspects as important.

Racism is another aspect 6that has impact society life in many places across the world. Blacks have faced much animosity from white counterparts in many parts of America and the United Kingdom (Gawer, 2014). Such social injustices have been a contributor towards the inequalities that exist within countries. Some individuals in society consume particular meals based on their choices, tastes and preferences. It is important to highlight that not all people in such economies can afford to access food remotely via the internet. Equally, such individuals cannot track their health developments based on meals that they take (Strachan, 2017). In essence, technology has significantly led to development of digital food cultures that have taken the world by storm. Individuals from any part of the world can train on how to cook particular means even though they do not come from the same cultural background. Economic production and materialism are useful concepts that should be considered when exploring culture within society. The fact that society is dependent on technology has changed the scope of operation in most sectors of the economy. People with less power have little ability to adapt to cultural changes in most societies (Sobande, 2019). As such, smaller groups in society will face difficulties in handling issues with inequalities in a significant manner. The United States is one of the countries that have adopted economic production as a strategy that can help reduce disparities in cultural practices that have impacted formulation of a popular culture.

Technology, Music and Popular Culture

Technology has impacted the development of the music industry in a significant manner over the last few years. Digital technology use in the music industry has done well to ensure that artists can sell their tunes to customers directly (Tatarchevskiy, 2011). One of the recent developments in the world of music is pop that has taken many by storm. Originally, pop music is linked to Black Americans in the United States. It is important to note that much has changed in the music industry and pop music adopted new strategies that have seen it gain more popularity (Lee, 2009). The development art based on technology is an illustration of how digital culture leads to the formulation of a popular culture. One of the recent developments in technology that has changed the world in one way or the other is the use of Digital Audio Workstation. Both artists and producers can use its interface to control the production of music in a significant manner. In essence, technology has been a pillar for improved music developments across the world. People can listen to music on their smartphones from remote locations (Strachan, 2017). Applications such as YouTube have made it easier for people to remotely access music of their taste. Such developments in the digital technology have led to formulation of a popular culture where producers and musicians apply technological advancements in promoting efficiency and efficiency.

Technology is essential in ensuring that musicians secure their intellectual property and avoid unnecessary theft. Digital developments in society are helpful in promoting and adding to existing devices that spice music (Sobande, 2019). For instance, use of live video recording has been helpful in promoting the quality of music that many artists make. Digital technology is a pillar towards change in society and the music industry has transformed in a significant manner. Multi-track recording is another important digital development that has led to change of pop culture in music production (Marsh, 2005). Initially, sound engineers and musicians had to record a whole track as one, which has since changed the scope of operations in the industry. Artists and sound engineers can do several separate parts of one song with the option and record it as one (Strachan, 2017). In essence, digital technology in music has led to changes that can since be termed as development of a popular cul6ture in the industry. Technology and digital culture across the world has led to transformations in the music industry in a significant manner.

Digital Culture, Technology and Social Interactions

Digital technology across the world has changed the way people interact and communicate on a daily basis. For instance, establishment of various social media platforms has changed the way people interact to a large extent. The interactionist sociological perspective can help explain how much has changed regarding interactions and communication. In the past, people used to meet and communicate with each other through conventional means that existed (Marsh, 2005). The development of social media and other aspects has changed the scope of operation in a significant manner (Lee, 2009). Platforms that are widely applied in communication include Facebook, Twitter, WhatsApp, Instagram and TikTok. Such platforms have been instrumental in helping people in society communicate in an efficient and convenient manner from remote locations. Facebook offers a messaging service that allows end users to communicate in private regardless of their location (Lupton and Feldman, 2020). Digital technology has changed the way and culture of communication in most societies. Large companies use such platforms to communicate with clients from different parts of the world. Traditional approaches to communication are not tenable in most circumstances as people prefer convenience and speed. Communication in society creates awareness and ensures that people have solved crucial problems that impact their wellbeing (Tatarchevskiy, 2011). Failure to administer the right communication approaches can be detrimental to passing of information from one place to another. Equally, digital approaches to communication have proved efficient in promoting reliability and faster decision making.

Companies have resolved to use of artificial intelligence as approaches that can promote business operations in the market. Artificial intelligence is used to capture and gather important information from various online platforms (Sobande, 2019). The culture of many societies has been impacted by developments in technology. Communities can communicate their intentions to the world regardless of the global location of an individual. In essence, technology has led to development of a digital culture that supports business operations (Marsh, 2005). For instance, communicating to clients who need feedback on a particular matter can be done by automated responses in the system. Facebook and other social media platforms have established systems that can provide feedback without needing the input of a human (Kent, 2020). The formulation of a popular culture has been influenced by internet use and digital practices in many parts of the world. People have developed a habit of communicating and interacting online unlike in the past when face-to-face communication was preferred.

Why Popular Culture Matters

It is important for the essay to establish technology impacts operations in various societies and the development of a popular culture. The first aspect that makes a popular culture important includes improved mutual co-existence in society (Lupton and Feldman, 2020). Culture is essential in helping communities interact with each other keep a high level of diplomacy. The fact that people communicate from remote locations without restriction is an indication that popular culture matters. People communicate more often through online digital approaches as compared to the past when conventional means were common. Communities that have popular culture have done well economically and in reducing inequalities that impact the wellbeing of people in society (Lee, 2009). Popular culture forms a basis for societal conformity and respect for one’s beliefs. Minority groups in most parts of the world can benefit from popular cultures as it echoes the practices and beliefs that are generally acceptable among a people (Deuze, 2006). Culture is an equalizer that makes each individual in society to feel equal as their counterparts as nothing makes anyone special. Each member has to comply and respect beliefs and practices of popular culture. In essence, popular culture promotes conformity in society and mutual co-existence among its members.

Cultural orientations in society define the beliefs and ideals of a people in a significant manner. Politicians across the world should embrace popular culture as a way of reaching out to individuals in society (Lupton and Feldman, 2020). Failure to do the same attracts further challenges that can lead to conflicts and misunderstandings in society. Societies that have been dominated by poor cultural orientations that do not accommodate multiculturalism face a challenge in maintaining a peaceful and respectable society (Deuze, 2006). There is a need to address the issue of cultural segregation that is affecting the growth and development of a popular culture. Popular culture matters to each society as one cannot connect with them without showing respect for beliefs and practices within a particular community. Popular culture is important has it has helped reduce the negative consequences that are associated with racism and ethnicity (Kent, 2020). Countries that have popular cultures such as the baseball game use it as an opportunity to interact and share with others. In essence, popular culture in most societies act as a way of uniting people and reducing the possibility of developing conflicts that can be detrimental to economic growth.

To sum it up, popular culture refers to a set of practices, beliefs and objects that are important to a particular community at a given time. For instance, the baseball game is an illustration of popular culture that can bring people together in a community. The essay explores the impact of digital culture and technologies in formulation of a popular culture. For instance, the establishment of internet has been a pillar that has led to development of a popular culture. The internet provides an opportunity for many in society to interact and share crucial aspects that affect life. For instance, popular culture can refer to practices in popular music and filming. Failure to embrace popular culture can lead to conflicts that should be handled as they can hinder economic progress. The interactionist theory, feminism and postmodernism can be used as theories to help increase the scope of understanding on the discussion topic.

Causey, M., 2007.  Theatre and Performance in Digital Culture: From simulation to embeddedness . Routledge.

Ceron-Anaya, H., 2010. An approach to the history of golf: Business, symbolic capital, and technologies of the self.  Journal of Sport and Social Issues ,  34 (3), pp.339-358.

Deuze, M., 2006. Participation, remediation, bricolage: Considering principal components of a digital culture.  The information society ,  22 (2), pp.63-75.

Gawer, A., 2014. Bridging differing perspectives on technological platforms: Toward an integrative framework.  Research policy ,  43 (7), pp.1239-1249.

Kent, R., 2020. Self-tracking and digital food cultures: Surveillance and self-representation of the moral ‘healthy’body. In  Digital Food Cultures  (pp. 19-34). Routledge.

Lee, J.Y., 2009. Contesting the digital economy and culture: digital technologies and the transformation of popular music in Korea.  Inter‐Asia Cultural Studies ,  10 (4), pp.489-506.

Lupton, D. and Feldman, Z. eds., 2020.  Digital Food Cultures . Routledge.

Marsh, J. ed., 2005.  Popular culture, new media and digital literacy in early childhood . Psychology Press.

Niemeyer, K. and Keightley, E., 2020. The commodification of time and memory: Online communities and the dynamics of commercially produced nostalgia.  New Media & Society ,  22 (9), pp.1639-1662.

Sobande, F., 2019. Woke-washing:“Intersectional” femvertising and branding “woke” bravery.  European Journal of Marketing .

Strachan, R., 2017.  Sonic technologies: popular music, digital culture and the creative process . Bloomsbury Publishing USA.

Tatarchevskiy, T., 2011. The ‘popular’culture of internet activism.  New Media & Society ,  13 (2), pp.297-313.

Waldfogel, J., 2018.  Digital renaissance: what data and economics tell us about the future of popular culture . Princeton University Press.

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Global Digital Cultures

Perspectives from south asia.

How digitalization is reshaping culture and communication in the twenty-first century

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• Table of Contents and Introduction

Description

Digital media histories are part of a global network, and South Asia is a key nexus in shaping the trajectory of digital media in the twenty-first century. Digital platforms like Facebook, WhatsApp, and others are deeply embedded in the daily lives of millions of people around the world, shaping how people engage with others as kin, as citizens, and as consumers. Moving away from Anglo-American and strictly national frameworks, the essays in this book explore the intersections of local, national, regional, and global forces that shape contemporary digital culture(s) in regions like South Asia: the rise of digital and mobile media technologies, the ongoing transformation of established media industries, and emergent forms of digital media practice and use that are reconfiguring sociocultural, political, and economic terrains across the Indian subcontinent. From massive state-driven digital identity projects and YouTube censorship to Tinder and dating culture, from Twitter and primetime television to Facebook and political rumors,  Global Digital Cultures  focuses on enduring concerns of representation, identity, and power while grappling with algorithmic curation and data-driven processes of production, circulation, and consumption.

Aswin Punathambekar  is Associate Professor of Media Studies and Founding Director of the Global Media Studies Initiative in the Department of Communication Studies at the University of Michigan. Sriram Mohan  is a doctoral candidate in the Department of Communication Studies at the University of Michigan.

“This is a fantastic volume on an important topic. Global digital culture is a growing field. This volume will set a new standard and become a core text.” —Guobin Yang, Grace Lee Boggs Professor of Sociology and Communication, University of Pennsylvania  

"...this is a valuable addition to the literature that has for decades been documented by the Global North." — Journalism & Mass Communication Quarterly - Usha Raman

"The essays in this volume perform the necessary work of contextualizing digital media usage in light of local pressures of representation, exploration, and aspiration." - After Image , Laboni Bhattacharya  "These essays represent exciting work being undertaken in South Asian media studies." -  After Image , Laboni Bhattacharya  - Laboni Bhattacharya

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Digital Culture

Lecturer in Psychology, Centre for Culture and Evolution, Brunel University London

• Published: 23 February 2023
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The diffusion of digital technologies triggered a radical departure from previous modalities of cultural transmission but, at the same time, general characteristics of human cultural evolution and cognition influence these developments. This chapter explores some areas where the contacts between cultural evolution research and digital media seem promising. As cultural evolution-inspired research on Internet phenomena is still limited, these areas represent suggestions and links with works in other disciplines more than reviews of past research in cultural evolution. These include topics such as how to conceptualize social influence online and how information spreads in social media; how digital media could enhance cumulative culture; and the differences between online and offline cultural transmission. The chapter will then briefly consider possible future directions: the influence of different affordances in different media supporting cultural transmission; the role of producers of cultural traits; and, finally, the effects on cultural dynamics of algorithms selecting information.

Introduction

Research on the effects of digital media on cultural dynamics is, not surprisingly, abundant and spans different disciplines. In this chapter, I will focus on research that is inspired by, or compatible with, cultural evolution, intended as a framework encompassing various evolutionary approaches to culture and cognition. In the digital age, our activities produce an amount of quantitative data that would have been unimaginable until a few decades ago. This availability has generated an explosion of computationally-oriented research on human behaviour and it allows digital companies to develop heavily data-driven business strategies. Data, however, and sophisticated computational methods, are not enough. Cultural evolution is in a privileged position to analyse cultural dynamics in the digital age. Cultural evolution is, differently from other approaches in human and social sciences, grounded in a quantitative methodology that promotes the usage of data produced by our digital activities. At the same time, it draws on a robust theoretical background from evolutionary biology and cognitive science, which should help to choose how to use these data and the questions worth asking.

The label ‘digital culture’ is a broad one. Digital media are media encoded in digital format, and their history can be traced back to the middle of the last century, with the invention of digital computers. Here I am discussing a more recent phenomenon, concerning first the diffusion of personal computers, followed by the widespread usage of internet, and finally by the ubiquitous connectivity allowed by portable devices such as smartphones. Below, I will refer interchangeably to ‘online’ or ‘digital’ culture (and media) to address the current stage of these developments.

Despite the rapid growth of the field of cultural evolution, research explicitly dedicated to the study of how the diffusion of digital online media impacts culture is still limited within this framework. From one side, general, possibly evolved features of cognition and common properties of cultural evolution constrain what kind of cultural artefacts succeed and how they develop, in digital media as elsewhere. On the other side, the diffusion of digital and online media impacts cultural dynamics, for example, making it possible to access a virtually unbounded number of individuals from whom to copy from (hyper-availability), or making high-fidelity transmission cheap, quick, and widespread (think of a social media ‘share’), in a way that was impossible even a few years ago (Acerbi, 2019a , 2016 ).

In what follows, I will examine some areas where the links between cultural evolution and digital media are starting to be explored. More than a review of previous research, the sections below explore ideas to develop, and hopefully offer suggestions for future work. The ambition is that cultural evolution could provide a promising way to look at these developments, and to frame precise research questions. I will first propose that a cultural evolutionary approach, with its emphasis on the adaptivity of social learning and communication, suggests a productive starting point to analyse the effects of social influence online, and I will explore how concepts from cultural evolution can be used to investigate the spread of information in social media. I will then move to one of the central ideas of the framework, that is, cumulative culture, and consider how features of digtial cultural transmission could impact it. The chapter will then examine how it is possible to compare explicitly cultural transmission offline and online. Finally, I will briefly consider some important topics regarding digital culture, mostly unexplored in cultural evolution: how different online media (e.g., different social media) may support different modalities of transmission; the importance of the intentions of the producers, or spreaders, of cultural traits; and the effects on cultural dynamics of top-down algorithms selecting information for us.

Social Influence Online

Research in cultural evolution has extensively explored how we select information when presented with choices. This stream of research (see e.g., Kendal et al., 2018 ) naturally fits with the interest in how information flowing through digital and social media influences us. The hyper-availability provided by online connectivity, coupled with the alleged persuasive power of celebrities, online ‘influencers’, and even algorithmically based campaigns of mass persuasion, have generated a widespread panic that is often associated with the early phases of the diffusion of new technologies ( Orben, 2020 ). How justified are these concerns?

Social learning—the acquisition of new ideas and behaviours through interactions with conspecifics—is extensively used by humans, and it appears ubiquitous in other species too. One of the central tenets of cultural evolution theory is that for this to be possible, social learning needs to be selective: drawing on insights from formal modelling showing that indiscriminate social learning is not more effective than individual learning, cultural evolutionists have developed the concept of social learning strategies, or cultural transmission biases, domain-general heuristics used to decide when, what, and from whom to copy ( Laland, 2004 ). Social learning strategies are simple rules, implemented at individual level, such as ‘copy prestigious people’ or ‘copy the majority’. These rules represent a first damper to indiscriminate social influence, offline or online. However, social learning strategies are effective only on average: copying the majority can be useful on some occasions but detrimental in others. The efficacy of these strategies lies explicitly in balancing precision and simplicity, and thus their outcomes depend on the circumstances.

In this perspective, it could be that the situation created by online social media is so unusual that social learning strategies are not effective in this context ( Barkow et al., 2012 ). This is an interesting question and it will be discussed more in the section Comparing Offline and Online Cultural Dynamics, but for now it is important to notice that recent work in cultural evolution is starting to emphasize a more nuanced approach to the usage of social learning strategies. For example, we do not blindly ‘copy prestigious people’, but we copy prestigious people when we can reliably associate their prestige with their success, and in a task we are interested in ( Brand et al., 2020 ). The current view is that social learning strategies are highly flexible, context-dependent, and subject to individual and cultural variations ( Kendal et al., 2018 ). Future work is required to establish whether a consistent theory based on social learning strategies can explain the full variability of empirical observations without losing predictive power.

On top of this, several experiments run by cultural evolutionists have shown that we consistently underuse social information, even when it would be useful for us to copy others ( Morin et al., 2021 ). While the reasons behind this pattern need to be further explored, this strongly goes against the idea of unbounded social influence, both online and offline: the problem seems not to be that we are too gullible, but that we are too stubborn, and we do not accept correct social information often enough.

Taking these observations into account, the integration of other evolutionary approaches to social influence is a promising direction. Other researchers have proposed that humans possess specific cognitive mechanisms for epistemic vigilance, for example, assessing the risk of being misinformed by others ( Sperber et al., 2010 ). This approach has a similar evolutionary rationale that the social learning strategies approach delineated above, but it draws on communication instead of social learning, it considers the possibility of deception and conflicts of interests (scarcely explored in cultural evolution), and it relies on a set of more sophisticated cognitive abilities, such as plausibility checking, trust calibration, and reasoning, used to decide whether to accept information coming from others or not ( Mercier, 2020 ).

How can all this be applied to online dynamics? A relevant case study concerns, for example, the spread of misinformation online. While much research has focused, in the past years, on its diffusion and on its purported deleterious effects (see e.g., Vosoughi et al., 2018 ), when considered within the global information ecosystem the amount of misinformation circulating online is surprisingly limited. Recent empirical studies estimated that misinformation represented between around the 0.15 per cent and the 5 per cent of the total information circulating on social media ( Allen et al., 2020 ; Grinberg et al., 2019 ; Guess et al., 2019 ; Osmundsen et al., 2021 ). These figures seem consistent with an image of humans as wary or flexible learners delineated by the evolutionary approaches to culture and cognition presented above, more than with one of gullible agents. Even more importantly, engagement with misinformation cannot be equated automatically with impact on beliefs and behaviours. Even if in certain contexts misinformation may be shared on social media as much as reliable information (see e.g., de Oliveira & Albuquerque, 2021 ), we engage with misinformation to signal political affiliation and group membership, as much as we do with reliable information ( Osmundsen et al., 2021 ), to socialize with our peers ( Berriche & Altay, 2020 ), simply because of funny or interesting ( Acerbi, 2019b ), and, in fact, to verify whether it is true, and to say it is not ( Tandoc et al., 2018 ). Various studies show that people engage with political misinformation of their same political slant, so that misinformation cannot be considered as a form of influence that changes their beliefs, but as information consistent with their previous ones ( Allcott & Gentzkow, 2017 ; Guess & Nyhan, 2018 ).

Regardless of the specific details, a cultural evolutionary approach suggests that we need to be sceptical, at least as a starting point, of gloomy accounts of the dangers of online social influence, and empirical data are mostly consistent with this stance. More importantly, a cultural evolutionary approach provides specific hypotheses that can be tested on online data and specific mechanisms that can be at play when we decide whether to accept or not information, providing a complex picture of social influence, offline and online.

The Spread of Information Online

Cultural evolution theory makes a broad distinction between two main reasons why a cultural trait spreads. On one side, cultural traits can be successful because of intrinsic characteristics. Everything else being equal, a more effective hammer is likely to spread more than a less effective one. A memorable, attention-grabbing story is likely to spread more than a dull one. These intrinsic characteristics generate what cultural evolutionists call content -based biases. On the other side, cultural traits can be successful because of contextual reasons, independent from their intrinsic features. A not-very-effective hammer can spread because is advertised widely; a dull story can have broad diffusion because a celebrity recounted it. These context -based biases are represented by the heuristics we briefly discussed in the previous section, like ‘copy the majority’, ‘copy prestigious people’, and many others ( Kendal et al., 2018 ).

The traces left by information spreading online can be used to test how cultural traits spread. Most research has focused on content: which features make social media posts or online news successful? This stream of research fits with comparable work in cultural evolution that isolates content that makes narratives successful, often using transmission chain experiments (more on this on Comparing Offline and Online Cultural Dynamics). In one of the first works in this area, Heath et al. (2001) found that urban legends containing more elements eliciting disgust (such as the presence of worms in McDonald’s hamburgers) were also more diffused on specialized websites. With an explicit cultural evolution approach, Acerbi (2019b) analysed the content of online articles classified as misinformation to detect the presence of elements previously highlighted in experiments: disgust, but also threat-related information, negative content, minimally counterintuitive elements, sex-related material, and social information. A main outcome of the analysis was that negative content was preponderant in online misinformation, about five times more common than positive one. The advantage of negative content has been also detected in social media, with an analysis of a large dataset from Twitter, showing that negative tweets were more likely to be retweeted after political events, both negative and positive ( Schöne et al., 2021 ). Similar results were found considering tweets from news organisations: negative affect was expressed more than positive, and predicted more engagement ( Bellovary et al., 2021 ).

The online advantage for negative information is supported by results of transmission chain experiments ( Acerbi, 2022 ; Bebbington et al., 2017 ) and it is consistent with the evolutionary rationale for which negative information, concerning dangers and threats, is more relevant than positive information ( Baumeister et al., 2001 ). However, other studies found that emotional content in general was predictive of online success. For example, analysing New York Times articles, Berger and Milkman (2012) found that articles with content that generated high-arousal emotions (both negative and positive) were shared more than articles with content evoking low-arousal emotions. Similarly, Brady et al. (2017) observed that the presence of words expressing moral emotions increased the probability for tweets to be retweeted.

Overall, it could be that both negative content and emotional content in general favour the spread of online information. Further analyses could explicitly investigate how emotional content is linked to the topics that are discussed, such as political or controversial topics, or misinformation versus reliable information. In addition, the intentions of the individual sharing information and the specific context of transmission are likely to be important: sharing New York Times articles with friends, as in the Berger and Milkman (2012) study, may be different than, say, an anonymous conversation on Reddit. Finally, quantitative content analyses of social media spreading have so far focused on emotional content, possibly because it is the easiest to identify automatically with the available software. More sophisticated computational techniques, such as topic modelling or machine learning (as in Brady et al., 2021 ), allow us to detect specific content in large datasets and will enrich our understanding of which content is favoured online.

Less research is dedicated to context-based biases, and practically none within a cultural evolution framework. The role of social media personalities, influencers, and the like in the spreading of cultural traits online is an open question. A relevant study using Twitter data ( Bakshy et al., 2011 ) found, for example, that the success of a tweet was correlated with the number of followers of the author of the tweet, but this measure can not disentangle the effect of ‘influence’—similar to demonstrator-based biases in cultural evolutionary theory terms—from pure availability, in other words the fact that a tweet coming from a user with many followers will simply have more exposure. In addition, the authors noticed that number of followers, together with a second measure called ‘local influence’ (indicating the number of past retweets an user received in the past from their followers), were in any case a poor predictor of future success.

Recent studies have highlighted that successful politically related content on Twitter is often correlated with out-group animosity or derogation ( Osmundsen et al., 2021 ; Rathje et al., 2021 ). If this suggests some connection with transmission biases studied in cultural evolution, it is not obvious to equate it with the role of strategies like ‘copying kin’ or ‘copying similar individuals’, which are mostly about selecting information.

Similarly, the role of frequency-based biases, such as ‘copying the majority’, is largely unexplored. Popularity in digital online media is often characterised by highly skewed distributions, with very few items that are very popular and many that are not. While this may suggest a popularity bias, the mechanisms producing these distributions need to be understood case by case. Such skewed distributions can also be produced by unbiased transmission, that is, by individuals copying each other at random without a preference for popular items, as common cultural traits are more likely to get chosen, with a self-reinforcing effect ( Bentley et al., 2004 ).

Finally, a promising methodology to disentangle the role of different transmission biases in online dynamics has recently been proposed by Carrignon et al. (2019) . They used individual based models to simulate the expected distributions of retweets given different learning strategies. They then used approximate Bayesian computation to compare model outputs with real data: in this way, the transmission bias behind the model that better fit the real data is likely to have generated them in the social media. Analysing a sample of confirmed and debunked rumours (from Vosoughi et al., 2018 ), Carrignon et al. (2019) concluded that it was not possible to find signatures of the transmission biases that they considered, and that an unbiased transmission model had a better fit.

Digital Cumulative Culture

Many animals use social cues to adjust their behaviour, but humans are considered the only species to have cumulative culture. While there are various definitions (see e.g., Mesoudi & Thornton, 2018 ), the central idea is intuitive: human culture accumulates innovations in a way that is not observed among other species and, iteratively, this process generates cultural traits that would be extremely unlikely to be invented by an isolated individual. Cumulative culture is not an automatic process. Empirical research and models have suggested factors that promote cumulative culture, including large population sizes, efficient social networks, and transmission fidelity ( Derex & Mesoudi, 2020 ; Lewis & Laland, 2012 ).

Today, much cultural transmission is supported by online digital media: how does this impact cumulative culture? A few studies have investigated relevant dynamics in the online domain. Youngblood (2019) tracked the spread of music samples among hip-hop and electronic producers and showed that, thanks to digital sampling technologies, their networks of collaborations are no longer constrained by geographical proximity. Müller and Winters (2018) analysed the evolution of Reddit Place, a social media experiment in which any registered user could place a single coloured pixel on a 1,000 × 1,000 pixels online digital canvas every 5–20 minutes for three days. The project involved 1 million individuals that placed more than 16 million pixels. The analysis tracked the increase in compressible graphic patterns, showing that the canvas moved towards a structured state, with many relatively stable and independent patterns.

These studies confirm that digital online media do increase the potential network where cultural transmission can happen and that, at least in some circumstances, online collaboration among many unrelated individuals can be successful. Cultural evolutionists, inspired by population genetics, have developed the concept of effective cultural population size. Effective cultural population size indicates the number of people potentially or actually involved in cultural transmission. The bigger the effective cultural population size, the more likely it is that complex cultural traits are not lost and effective inventions retained, promoting cumulative cultural evolution ( Derex & Mesoudi, 2020 ). While the growth of effective cultural population size is a historical process, and it has been impacted by other technological innovations, such as writing, printing, or the increasing accessibility of travel, online media have a tremendous impact, with virtually everyone in Western countries having daily Internet access. When considering global usage, marked differences remain, but the gap is narrowing, with many countries showing significant growth. Incidentally, what will be the consequences of the diffusion of technologies related to internet to the majority of people on the planet is a compelling question for the future ( Arora, 2019 ).

Another aspect that links cumulative cultural evolution and the diffusion of digital media is that digital media provide a cheap, fast, and effective way to transmit information. Empirical results suggest that fidelity of transmission is impacted by several factors and that high-fidelity transmission cannot be considered the default condition. Cultural transmission chain experiments, for example, show that oral transmission is generally a low-fi process, with information getting rapidly lost during the process ( Mesoudi & Whiten, 2008 ). As for small effective population sizes, the same risk is present with low transmission fidelity: complex cultural traits can get lost in the process of transmission, negatively impacting cumulative cultural evolution. Transmission fidelity can, however, be increased by ‘fidelity amplifiers’ ( Acerbi, 2019a ) associated with the process of transmission. Cognitively attractive features can make some narratives easier to remember ( Stubbersfield et al., 2017 ), rhymes and repetitions can help the memorization and repetition of stories, written instructions can be preserved better than oral ones. In this perspective, digital media provide several fidelity amplifiers: they possess the features that make analogue writing effective, but also many others, including the possibility of direct interactions (e.g., comments associated with an online recipe) or to include different media easily (e.g., YouTube video tutorials).

Increased effective cultural population size and fidelity of transmission do not guarantee improvements in cultural cumulation. It has been proposed that more than size is the typology of the social networks that affects cumulative cultural evolution ( Derex & Mesoudi, 2020 ). Likewise, fidelity of transmission (coupled with cheap storage) could simply, as it happens, increase exponentially the size of the long tail of cultural traits that are preserved, but not contributing to any process of cultural cumulation. For any successful, and possibly effective in cultural transmission, YouTube video tutorial, there are millions of unwatched videos online.

Few studies have explicitly considered the effect of digital media on cumulative cultural evolution. In a preliminary work, Pianzola et al. (2020) investigated the case of online fan fiction, where non-professional authors expand narratives from existing works of fiction. Fan fiction is an interesting case, because it has been made possible, in its contemporary form, by online media, because is strongly collaborative, and because concerns a domain—art—where the extent of cultural cumulation is debated ( Tinits & Sobchuk, 2020 ). Pianzola et al. (2020) found that stories in Harry Potter fan fiction accumulated cultural traits (measured as unique tags) through time, suggesting an increase in complexity, and that more recent stories were more liked than earlier ones, suggesting a possible improvement, two features that are often associated to cumulative cultural evolution.

Further research is needed to investigate whether, and in which conditions, digital online media can impact, positively or negatively, cumulative cultural evolution. The availability of data regarding online communities represents by itself an advantage, and these data could be used to test specific hypotheses about, for example, demography and cumulative cultural evolution. To pinpoint the specific role of digital media, it would be important to compare the features of cumulative cultural evolution in similar domains, but with or without digital support. Another possibility is to explicitly design experiments in which skills are transmitted in ‘traditional’ forms of transmission, such as oral descriptions or observations of demonstrators, and in form of transmission made possible by digital online media, such, for example, instructional videos that can be replayed and paused.

Comparing Offline and Online Cultural Dynamics

In the sections Social Influence Online and The Spread of Information Online, we mostly discussed how general cultural evolution findings can be applied to the online domain. In the following section, Digital Cumulative Culture, we started to explore how features of digital cultural transmission, such as the hyper-availability provided by online connectedness and the increased fidelity of transmission, can impact on cultural evolution itself. In this section, we will expand on this and consider more explicitly some differences between offline and online cultural dynamics.

Another feature that characterises online cultural transmission can be called ‘explicitness’. Social media posts are accompanied by information such as the user name of the person who posted it; the number, and often the names, of users that liked or shared (the terminology varies in different social media) the message; comments on the post from other users. Products, including cultural products, such are recipes or songs, are scored, rated, and reviewed publicly. Given the abundance of information available online, we are often presented with top lists of the items we are interested in, as scored by other users and algorithms.

As mentioned above, when evaluating social information, we use cues to infer from where this information is from, or who else is using it. These cues are mostly implicit. One strategy commonly studied in cultural evolution is conformity (see van Leeuwen and Morgan, Chapter 15 in this volume), technically defined as a disproportionate tendency to copy the majority, meaning that we should have a probability to copy a cultural trait higher than its frequency (to simply ‘copy the majority’, it is sufficient copying at random, since a common behaviour will have more probability to be selected). In a traditional setting, the majority needs to be inferred from a sample of observations: what are other people doing? But in social media we can have an explicit, immediate, and precise quantification: how many people liked or shared a post? What are today’s ‘trending’ topics? Something similar happens for prestige bias. In the cultural evolution account, we observe to whom other people pay respect or deference to infer prestige, and act accordingly (See Offord and Kendal, Chapter 16 in this volume). With online media, we can access effortlessly to information provided by global celebrities or politicians, or we can directly quantify ‘prestige’, for example with the number of followers one user has.

What are the consequences for cultural evolution? One could hypothesize that explicit cues, for example of popularity or prestige, could increase our reliance on these strategies, or even make their output more reliable, as their usage is based on accurate assessments. On the other side, the introduction of such explicit cues is a very recent phenomenon, and we may still need to evolve the appropriate tools culturally to make sense of them. A few studies that tried to address the question directly suggest that the effect of explicit cues does not result in a reinforcement of the tendencies to copy the majority or prestigious people. Acerbi and Tehrani (2018) found, in an online experiment, that participants did not prefer quotes attributed to famous authors (as opposed to random names), and only partially followed popularity cues: they preferred quotations that were presented as chosen by many other participants, but not in the ‘disproportionate’ way that characterises conformity. In an influential paper, Salganik (2006) describe the result of a large-scale experiment, where participants were divided into separated ‘worlds’, all of them listening to the same pool of previously unknown songs. Songs were rated by participants but, here is the catch, the ratings were only shared within worlds. The results show that different songs became successful in different worlds, driven by popularity ratings. At the same time, however, there was a correlation between the success of the songs and their success in a control condition, where ratings were not shown, demonstrating that the information on popularity was only partially driving the dynamics. The effect of explicit cues is an open question, awaiting more research, possibly using also non-experimental data, for example from social media, as well as considering cultural traits with adaptive value, unlike listening to songs or choosing preferred quotes.

Another aspect that differentiates online and offline transmission, which we already considered, is fidelity. As we mentioned above, most of the results about what content is favoured in cultural transmission come from transmission chain experiments. Transmission chain experiments are controlled version of the telephone game, where participants need to hear (or read) a story from another participant, memorize it, and repeat it to the next participant in the chain (see Mesoudi, Chapter 6 in this volume). This is very different to what happens in online transmission, where one does not need to memorise and repeat, but only choose whether to further share (and sometimes willingly modify) some information.

Some research is starting to focus on the details of transmission chains experiments, to address how they compare to real-life transmission dynamics. Eriksson and Coultas (2014) divided the transmission into three phases, ‘choose-to-receive’ (do participants want to read a story or not?), ‘encode-and-retrieve’ (the standard transmission chain procedure), and ‘choose-to-transmit’ (do participants want to transmit the story they read or not?), and found that the content they were interested in (disgust) was favoured in all phases, even when considered separately. Stubbersfield et al. (2015) and van Leeuwen et al. (2018) also used a similar set-up to test the effect of various types of content in the different phases of transmission. Stubbersfield et al. (2018) asked instead participants to modify the content of the material purposively when transmitting it, to make it more appealing. Acerbi (2022) directly compared content effects in a set-up similar to standard transmission chains versus online sharing, and found that, while negative content was favoured in both, results were less conclusive for content eliciting disgust and threat-related content. A possible suggestion from this last study is that content biases could be stronger when information needs to be memorised and repeated than when it is not needed. This is consistent with the idea that content biases influence cognitive processing and reproduction but, possibly counterintuitively, suggest that online sharing should be less subject to cognitive content biases than oral transmission.

More broadly, studies that explicitly compare offline and online cultural dynamics are also important to establish causal relationships between the effects we observe and the fact that cultural transmission is digitally supported. Above we highlighted, for example, that negative content is favoured in social media, but this seems to be a more general property of transmission that we observe also in other contexts. The claim that social media, by themselves, favour negative content is thus probably unwarranted. Similar claims, such as that social media favour the spread of misinformation, or of emotional content, need to be evaluated in the same way. Controlled experiments can isolate the features of social media that one considers as important for the effect, be them built-in fidelity (as in the previous example), speed and ease of diffusion, the possibility of feedback (‘likes’, ‘share’), and check whether the effect persists or not when they are not included in the transmission set-up.

Other Directions

Affordances of different media.

In the previous section, we discussed that it is important to take into account the specific features of online transmission. We cannot automatically transfer in the digital realm what we know about cultural transmission in general and, conversely, we cannot conclude from the observation of something happening in the digital realm that this is caused by the digital support. One can also go further, and discriminate among different digital media, or even different social media. At the beginning of this chapter, we pointed out that the ‘digital culture’ label is a broad one. ‘Digital’ cultural transmission can be implemented in various ways: social media, emails, online chats, sharing newspapers articles or, as it may be happening now, reading an academic chapter in an online published collection. All these activities imply different interests, digital affordances, and people involved.

Consider, for example, the research mentioned above, showing that the most shared New York Times articles were not characterized by negative emotion, but by high-arousal emotions, or content that was rated by participants of the study as ‘awe-inspiring’ ( Berger & Milkman, 2012 ). This goes against the seemingly robust finding of the advantage of negative information in social media. How can we make sense of this discrepancy? One possibility is to consider that we are dealing with two different contexts. Sharing New York Times articles with friends by email (as considered in this research) is a very different activity than posting something on social media. In the former we are specifically targeting someone, and a someone known to us, and we possibly expect their reaction, and so on. In the latter, the target is indiscriminate, and we can even be anonymous. In addition, subscribers of the New York Times are a very specific demographic, more educated than average, and more left-leaning. Could these differences explain the different outcomes?

This is a single example, but the same holds at various levels, even for different social media. Instagram is optimised for posting, sharing, and editing pictures, TikTok for videos, and Twitter mostly for short texts. Messaging services, such as WhatsApp, are altogether different. While in some occasions it is useful to zoom out and test general claims about ‘online’ or ‘digital’ culture, in others we may want to be more specific, and consider the fine-grained affordances offered by social/digital media and who their users are.

The role of producers of cultural traits

To explain the success of cultural traits, cultural evolutionists generally focus on the interests of the receivers. Social learning strategies are heuristics used by the receivers of cultural traits to decide whether to copy or not. The attractive features of content mentioned in this chapter, such as negative content, threat-related information, and so on, are considered attractive to receivers. It has recently been suggested that the role of producers of cultural traits has been partly overlooked, and that it is essential to explain cultural dynamics ( André et al., 2020 ).

Digital media, as much as they changed the way in which information is transmitted (which has been the main focus of this chapter), undoubtedly also changed how information is produced. As clichéd as it is, online digital media did allow an unprecedented number of people to record and share information. Social media users are sensitive to the reactions to their activity ( Lindström et al., 2021 ), and we need to take into account their interests when considering online cultural dynamics.

For example, there does not need to be a correlation between what is consumed and what is shared (see e.g., Bright, 2016 ). The two behaviours are very different: to explain cultural success online we need to consider not only what users want to receive but also what they want to share. Reputational management may have an important role in online dynamics, where information is potentially available to a large number of other people. Altay et al. (2020) explained the limited spread of online misinformation (see section Social Influence Online), with the fact that, even if some pieces of information may be attractive for users, sharing them could be detrimental to their reputation, exemplifying a clear contrast between the interests of the same users as consumers or producers (sharers) of cultural traits.

In this chapter, we discussed how the inclinations and the interests of consumers (and producers) of cultural traits, together with the features of digital media, determine the dynamics of the online spread of information. However, we did not consider what is probably one of the strongest influence of the digital environment, and certainly a radical cultural evolutionary novelty: the algorithmic control of the information we have access to. Algorithms are necessary to select information among the enormous amount that is present in internet or in a specific social media. However, the way algorithms do this is bound to have strong consequences on which cultural traits are successful.

One would expect, given that the interest of social media platforms is keeping users ‘hooked’ as much as possible, that the algorithms implemented would amplify the tendencies that we examined above. Thus, to exemplify, if we tend to prefer negative information, an effective (from the platform point of view) algorithm should present, on average, more negative information. However, it is unclear what are the consequences of this amplification, and if it works in practice: as negative information already capture users’ attention, presenting too much of it could be futile, or even having the opposite consequences.

In addition, one could legitimately argue that the goal of algorithms implemented by social media should not be hooking users in but something else, and that algorithms should be planned openly and collectively. In this case, the knowledge accumulated in evolutionary approaches to culture could be essential to design and test algorithms that select information online. The main problem for this direction of research is that while some social media (e.g., Twitter) have been open when sharing data about the information circulating on the platform, there is much less openness regarding the way algorithms operate, and indirect strategies need to be used to estimate the effects of algorithmic curation (e.g., Bartley et al., 2021 ; Huszár et al., 2021 ).

Acknowledgements

I would like to thank the editors of the Oxford Handbook of Cultural Evolution for inviting me to contribute with a chapter. Oleg Sobchuk and Jamie Tehrani provided useful feedback on previous versions of this chapter. Finally, some of the ideas discussed here (especially in the section Other Directions) were stimulated by the discussion in a ‘Cultural Evolution in the Digital Age’ Book Club organized by the International Cognition & Culture Institute in 2020. I would like to thank the organizers, Tiffany Morisseau and Dan Sperber, and all the participants.

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Digital culture

Digital culture refers to culture shaped by the emergence and use of digital technologies.

What is digital culture?

Digitalisation has become a particularly pervasive influence on culture due to the emergence of the internet as a mass form of communication, and the widespread use of personal computers and other devices such as smartphones. Digital technologies are so omnipresent around the world that the study of digital culture potentially encompasses all aspects of everyday life, and is not limited to the internet or modern communication technologies. 

While it would be artificial to distinguish clear-cut eras distinct from each other, culture shaped by digitalisation differs from its predecessors, i.e. what have been called print culture and broadcast culture, in a number of different ways. For instance, digital technologies have enabled more networked, collaborative and participatory forms of culture. Following Miller (2011), the specific characteristics of digital culture can be explained with the kinds of technical processes involved, the types of cultural form emerging, and the kinds of experiences digital culture entails.

Digital Culture and technical processes

In digital technologies, information is represented in numerical code. In practice, this means that digital material is easily modifiable and can be easily compressed (Miller 2011, 15). Practical everyday examples of this include the use of Photoshop for easy modification of images, and the storing of large amounts of information in e.g. smartphones. Unlike in broadcast culture, media are also networked and interactive, and so-called user-generated content has emerged as a cultural phenomenon to blur the boundaries between senders and receivers, or broadcasters and audiences, of media content. For instance social media platforms such as Facebook, and blogs and online forums host massive amounts of user-generated content.

The technical infrastructure also enables the hypertextual nature of digital media, as links can be created between different nodes of content. Hyperlinking is indeed one of the primary ways of organising content online. Yet further central features of digital material enabled by the technical processed involved are its automated and databased nature. Digital databases, like any database, have their own specific ways of storing, retrieving and filtering data, and turning that data into meaningful information. Digital databases are much more flexible than pre-digital ones, and an essential component of many everyday activities such as using an online search engine or a social media platform.

This also relates to the process of automation mentioned above. Many digital objects are created out of databases through automated processes. This also allows for personalisation of content. In practice, for instance social media feeds, recommendation systems and personalised advertising online are the result of such automated, algorithmic processes. (Miller 2011, 14-21) Due to the ubiquitous presence and immense influence of such processes, some have characterised present-day culture as ‘ algorithmic culture ’.

Cultural forms

Given that digital material is easily copied, spread and modified, digital cultural products are potentially in a constant state of ‘becoming’, in some respects more adequately described as processes rather than finished products. This is why for instance the established cultural form ‘narrative’, along with authorship, has been problematised in networked, hyperlinked digital environments: products are never complete, reading paths are hyperlinked and networked, and relationships between creators and audiences often anti-hierarchical and products collaborative constructions. (Miller 2011, 21-30) Collaborative digital art, online fan fiction and internet memes are just some examples of such present-day cultural production.

Digital technologies have also influenced the links between objects, space and time. (Miller 2011, 22-24) Objects can be easily not only modified, but also recontextualised, and objects from different historical and spatial contexts can be brought together to articulate something new or to create an ensemble of objects. For instance, music or film and TV streaming services – often also in a personalised way enabled by databased automation – are popular realisations of this. The shrinking of distance between audiences and art objects is another typical example: not only is cultural participation more democratic due to the instant availability of works of art, but also the means of producing e.g. moving image and visual cultural products and making them available to broader audiences have become more accessible forms of cultural participation. Virtual reality technologies can be expected to further transform cultural forms and participation.

Digital experience

It is still common to have a distinction being made between the ‘virtual’ and the ‘real’. This is a misleading distinction: even though virtual environments are intangible, this does not mean that they are not ‘real’. Our vocabulary also tends to reify clear distinctions between the ‘virtual’ (or online) and ‘offline’: terms such as ‘cyberspace’ and ‘meatspace’ have appeared to draw these distinctions while our experience is of both simultaneously. However, for instance in discussions regarding online bullying , it has been suggested that the specific kind of presence (distant, with lack of face-to-face contact; also called ‘telepresence’) enabled by digital technologies makes the threshold for people to abuse others lower. Virtual worlds and virtual reality also allow for a type of experience called simulation – immersive experience brought about by the creation of a model of a world, sometimes imitating the offline world. Second Life is an example of a hugely successful virtual world. Virtual experiences, as was the case with e.g. Second Life, are sometimes dismissively discussed through the familiar distinction between representation and simulation. The latter is here seen as somehow less authentic or real, pulling participants away from the ‘real’ reality. Video games are another example of a digital cultural medium that can produce immersive experience. (Miller 2011, 30-41)

Digital culture and new types of research

Understanding digital culture requires novel, innovative forms of research, and new approaches such as the broad field of digital humanities, digital hermeneutics, and digital ethnography have emerged to advance our understanding of culture shaped by digitalisation.

Miller, Vincent 2011. Understanding digital culture . London: Sage.

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Digital Culture & Society

• Online ISSN: 2364-2122
• Print ISSN: 2364-2114
• Type: Journal
• Language: English
• Publisher: transcript Verlag
• First published: September 30, 2015
• Publication Frequency: 2 Issues per Year

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Digital culture essay

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Digital Culture

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How do information and info sharing impact the digital culture of todays globe?

This issue can greatest be solved by understanding the ways in which todays digital lifestyle uses information. Grassegger and Krogerus remember that Big Info is the big elephant in the digital area: this is the assortment of information on every Internet end user on the planet, stored and provided so that present day advertisers can easily market their organizations goods exclusively to Internet internet browsers. Those advertisings that pop up everywhere you go, whatever type of internet site youre upon, that manage to know precisely what type of product youre at the moment interested in? They will know what youre interested in because your personal surfing habits will be being viewed are noted: thats what Big Data is. As well as its also a lot more than thatbecause today even your Amazon Fire is seeing and tuning in: your cellphone is being attentive to where you go when your travel around. Google is definitely recording the every motion. As Grassegger and Kregerus state, Big Data means, in essence, that everything we do, both on and offline, leaves digital traces (3). Those footprints are monetizedand they are also utilized to pry into the private lives of individuals.

Hence, the world moved from allowing for privacy most of the time where individuals can be relatively certain to be unobserved to being a universe where also private activities are watched and introduced into the general public in one way or another. What is even more interesting is that some individuals participate in this data sharing process intentionally. For example , various teens get on social media platforms and publicize their exclusive lives: they embrace the private can be public way of living of digital culture, in respect to Zaslow (Surveillance and Privacy).

As a result, information plus the sharing of information have afflicted the digital culture of todays world by making this more ubiquitous, more invasive, more incredibly elusive, and even more omniscient if that is possible. It is as though anything were being viewed, and as someone living in today’s world, where technology is a component to every means of human activity it seems like, cannot avoid the digital eye a large number of simply shrug their shoulder muscles: if you cannot conquer them, join in. So Big Data and the purveyors than it are allowed to rule. Digital tradition, it appears, is usually thus regulated by the man lurking behind the curtain: call him Zuckerberg; phone him Bezos; call him Schmidt. No matter what name you choose, just know that he great platform will be watching the flow of information and using that stream to advantage themselves and their stakeholdersand you participate in that process just be having a phone, a laptop, or a discussion with Siri.

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Living in a Digital Culture Essay

• Author: arsalan
• Posted on: 10 Jan 2020
• Paper Type: Free Essay
• Subject: Human Resource And Management
• Wordcount: 1378 words
• Published: 10th Jan 2020

Digital culture is connected with the rapid transformation in societies, affecting various technical and societal revolutions in a shockingly small extent of time. In this new digital era, computers are the vital sources by which the massive quantities of information that enormous technical and logical tasks necessitate are achieved and operated (Creeber and Martin 5). It can produce an advanced cyberspace democracy that means an extended open domain which is reduced in academics and little superior and claims the practice of new reachable kinds of language and discourse than those which intellects have been practiced to (Creeber and Martin 6).

Although there are many advantages of this digital culture but yet it has numerous effects on us. This trend in the direction of global integration creates a world of continuous increase of dissimilarities among the communities. (Creeber and Martin 5). According to some researchers, digital culture has not been a promoter of participating culture; rather the Internet has developed to be a dangerous and uncontrollable technology that permits profanity, extreme sacred or political intolerance and unauthorized computer users or viruses to weaken the public culture repeatedly. Administrators from China, Iran, and other countries have got critique for repressing websites, secretly observing on Internet operators and bullying bloggers. IT firms like Google, Microsoft, and Cisco Organizations have subsequently been made to protect their industries in such states, alleged of disregarding civilian rights about merely taking full advantage of returns (Creeber and Martin 6).

The main argument of this topic is that digital culture in our real lives is transforming even the best intellectual amongst us into trivial intellectuals incapable of involving in profound thought. It has affected our reading skills like it’s been messing with our minds and remodeling our memories. The thinking process has become slow and continuously transforming. In the past, people used to engage themselves in a book or a lengthy article very quickly and spent hours on reading it in curiosity. Such in-depth and amused reading has become a rare case. People lose their concentration after two to three pages and start looking towards something new to do. Hence, the extended passage that used to be natural and habitual has converted into a struggle (Carr n.p).

Such struggle is due to the time people contribute online, exploring and surfing. The Internet has become a God gift for the people. The research that previously used to take several days for searching the relevant material in the libraries can now be prepared in few minutes. People just have to do little Google explorations, specific rapid clicks on the links, and get the revealing detail or accurate assessment which they wanted to research, but these links don’t merely direct toward related works (Carr n.p).

The Internet has been becoming a worldwide platform. The benefit of having an instant approach towards such an immensely increased store of material is a lot, and they’ve been extensively imparted and appropriately approved. But that benefit has to pay value. As the media theorist, Marshall McLuhan observed intellectual people and identified that such medium is not merely submissive platforms of material. They are the source to provide the content for thinking, but they also modify the practice of thought and fragmenting away from the ability of people to focus and anticipate. The extent to which people use the Web, the more they have to struggle for concentrating on lengthy pieces of material. Many other writers have also claimed that their thinking process has been altered due to the Web. They have argued that they can now only skim through the lengthy articles (Carr n.p).

According to a recent online study behaviors, led by researchers from University College London, it is clear that consumers are not reading which is accessible by the computer in the old-fashioned intellect; certainly there are marks that modern procedures of reading are evolving as consumers “power browse” horizontally, however, headings, subjects pages and summaries going for rapid successes. It nearly looks like that they go online to evade reading in the old-fashioned intellect (Carr n.p).

We are not shaped merely by what we read, but we are transformed the way we understand. When we read online, we incline to become more translators of material. Reading is not a natural ability for humans. We have to decode our thoughts how to interpret the representative words we look into the language we recognize. According to James Olds, a professor of neuroscience, the mind has the aptitude to condition itself on the fly, changing the approach it performs. Some neurologist’s claim that the variation in our minds also happens at the biological level (Carr n.p).

The Internet, an incalculably important computing method, is incorporating best of our other knowledgeable machinery. It’s adding to be our guide and clock, our printing media and typewriter, our calculator and handset, and our radio set and television. It encloses the material with the material of the whole press it has ingested (Carr n.p).

There is a countertendency to assume the most awful of each new device. In Plato’s perception, people visit to count on the written expression as a temporary for the information they used to have in their minds; they would terminate to work out their commemoration and turn out to be vague. And since they would be capable of obtaining an amount of material without appropriate training, they would be assumed very well-informed when they are for the entire part pretty uninformed. Writing and reading would outgrowth renewed thoughts, and enlarge human information. Easy obtainability of records would indicate intelligent idleness, creating humans less severe and fading their attentions (Carr n.p).

Works Cited

Carr, Nicholas. “Is Google Making Us Stupid?”  The Atlantic , Atlantic Media Company, 27 Oct. 2017, www.theatlantic.com/magazine/archive/2008/07/is-google-making-us-stupid/306868/.

Creeber, Glen, and Royston Martin.  Digital Culture: Understanding New Media: Understanding New Media . McGraw-Hill Education (UK), 2008.

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