Studying Populations of Online Communities

While the large majority of published research on online communities consists of analyses conducted entirely within individual communities, this chapter argues for a population-based approach, in which researchers study groups of similar communities. For example, although there have been thousands of papers published about Wikipedia, a population-based approach might compare all wikis on a particular topic. Using examples from published empirical studies, the chapter describes five key benefits of this approach. First, it argues that population-level research increases the generalizability of findings. Next, it describes four processes and dynamics that are only possible to study using populations: community-level variables, information diffusion processes across communities, ecological dynamics, and multilevel community processes. The chapter concludes with a discussion of a series of limitations and challenges.

Revolutionizing Mental Health with Social Media

Social media platforms have emerged as rich repositories of information relating to people’s activities, emotions, and linguistic expression. This chapter highlights how these data may be harnessed to reason about human mental and psychological well-being. It also discusses the emergent role of social media in providing a platform of self-disclosure and support to distressed and vulnerable communities. It reflects on how this new line of research bears potential for informing the design of timely and tailored interventions, provisions for improved personal and societal well-being assessment, privacy and ethical considerations, and the challenges and opportunities of the increasing ubiquity of social media.

Propagation Phenomena in Social Media

Social media and blogging services have become extremely popular. Every day hundreds of millions of users share random thoughts, gossip, news, and thoughts on notable social issues. Users interact by following each other’s updates and passing along interesting pieces of information to their friends. Information therefore can diffuse widely and quickly through social links. Information propagation in networks such as Twitter and Facebook is unique, in that traditional media sources and word-of-mouth propagation coexist. The availability of digitally logged propagation events in social media helps one better understand how a wide range of factors that are essential in communication, such as user influence, tie strength, repeated exposures, mass media, and agenda setting, come into play in the way people generate and consume information in modern society. This chapter reviews the roles different types of users of social media play in information propagation as well as the resulting propagation patterns. It also discusses specific examples, including the spread of social conventions and identifying topic experts in social media, in an effort to bring about better understanding of the characteristics of propagation phenomena in large social networks.

Dynamical Processes in Time-Varying Networks

Networks in almost any domain are dynamical entities. New nodes join the system, others leave it, and links describing their interactions are constantly changing. However, due to the absence of time-resolved data and mathematical challenges, the large majority of research in network science neglects these features in favor of static or mean-field representations. While such approximations are useful and appropriate in some systems and processes, they fail in many others where the co-occurrence, duration, and order of contacts are crucial ingredients. This chapter presents a review of recent developments in the study of temporal networks and dynamical processes unfolding on their fabrics. It focuses in particular on activity-driven networks as an empirically motivated and analytically tractable class of models of the time-varying network. Within this framework the chapter studies the effects of temporal connectivity patterns in random walks, the epidemic model, and the rumor spreading model. The results highlight the striking impact that temporal correlations have on dynamical processes taking place over time-varying networks. The chapter ends by considering future research directions and challenges in this important area.

Dynamics of Attention and Public Opinion in Social Media

Sociotechnical systems such as online social media play a central role in today’s society, connecting millions of people all over the world. From a research perspective, a multitude of studies have gathered data from these environments to frame and unveil major questions on human social behavior. The goal of this chapter is to overview some theory of social communication behaviors, attention, and opinion formation in techno-social systems and their effects on individuals’ and group behavior. Examples of data-driven studies on large social media illustrate how users of techno-social systems behave during social protests, how they engage in political conversation, how they contribute to diffuse misinformation, and how they react to the spreading of fear and panic during a crisis. A quantitative analysis of the Twitter conversation during two global events (the Gezi Park protest in Turkey and the 2014 Ebola crisis) is presented as a case study to illustrate these phenomena. Understanding the dynamics of attention and opinion formation online allows people to build safer social media environments, hindering the spread of misinformation campaigns, hate speech, and stigmas.

Digital Mapping of Urban Mobility Patterns

Achieving accurate measurements of mobility and where people spend time is an essential step toward understanding how environments influence people’s impressions, actions, well-being, and health. But identifying where people are located in space and time and drawing from these data conclusions about what people actually experience is a challenge. Advances in communication technologies are creating possibilities for research today that even recently would not have been possible. This chapter reviews a classic study in the field of mobility pattern research, demonstrates the interest of mobility patterns to investigators of geography and health, and describes how geographic information systems and Global Positioning Systems are being used to better understand the complex relationships between people’s physical locations and health outcomes. The chapter concludes with predictions about how advances in communication technology will shape future research.

The Neuroscience of Information Sharing

Information sharing is a core human activity that catalyzes innovation and development. Recent advances in neuroscience reveal information about the psychological mechanisms that drive sharing, with a particular focus on self-relevance, social cognition, and subjective value. Based on these insights, this chapter proposes a structural model of the neurocognitive and psychological processes that drive sharing decisions, called value-based virality. Further, it maps existing knowledge about neural correlates and moderators of thought processes linked to individual and population-level sharing events and outcomes and suggests avenues for future investigation. Finally, the chapter discusses the potential of the neuroscience of information sharing to interact productively with other methodological traditions such as computational social science. Initial neuroimaging studies of information sharing provide insights into psychological mechanisms that were previously inaccessible. With the development of more realistic experimental setups and multimethod designs, future efforts promise advances toward a unifying theory of why and how people share information.

The Ethics of Digital Research

With all the important changes to methodology that research on networked communication brings, a key dimension that must be addressed is how to conduct research ethically. This chapter introduces section VI of the Handbook and reviews some of the key challenges that arise when doing digital research. This introduction draws from the many conversations the author had with various stakeholders about the the key issues surrounding the Facebook Emotional Contagion study, and it uses that discussion to highlight the main contributions of the chapters in this section. Some of the challenges considered include the evolving research ecosystem, changes in privacy practices, informed consent, heterogeneous populations and cultures, and technical and legal issues.

Understanding Social Dynamics Online

The last two decades have witnessed dramatic advancements in technologies that support human social practices. The chapters in this section focus on the role of person-centered networks as they are articulated, reinforced, and shaped by social media and other online communication technologies. By combining new data sources and existing social theory, the authors of these chapters offer fresh perspectives and articulate promising future pathways for research exploring the intersections among social networks, social capital, and social interactions. As these chapters illustrate, this is an exciting time for scholars who want to design and build technical interventions that will make a difference in the world, for those who welcome the insights afforded by new sources of data, and for those who are eager to re-engage with established theories in productive ways.

The New Dynamics of Organizational Change

Organizational change is well established as an important area of academic research. Across disciplines, from communication to sociology to management, scholars have produced a wide array of notable works examining various facets of organizational change. In recent years, however, advances in methodology and access to large data sets have opened up innovative avenues of research. This chapter examines new dynamics of organizational change, illustrated through a case study of the evolution of the news media industry in the United States. Many processes of organizational change are still based on traditional theories and established dynamics, but extant research and the present case study demonstrate that new technology and emergent patterns of communication lead to the development of new dynamics for coordination and control of information flow as organizations change over time. The chapter concludes with guidance and future directions for this evolving domain of scholarship.