ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data.

This post builds upon the 2015, and 2017 editions of this post, captures key trends and events which are shaping social media research for social scientists and provides a collection of research methods and tools for the analysis of social media data.

A growing body of scholarship acknowledges the increasing influence of global forces on social institutions and societies on multiple scales. We focus here on the role of globalization processes in shaping collective action and social movements. Three areas of global change and movements are examined: first, long-term global trends and collective action; second, research on national and local challenges to economic globalization, including backlash movements and the types of economic liberalization measures most associated with inducing oppositional movements; and third, the emergence of contemporary transnational social movements. In each of these arenas we address debates on diffusion, intervening mechanisms, and the outcomes of collective mobilization in response to global pressures.

he most important impacts of social movements are often cultural, but the sheer variety of potential cultural impacts—from shifts in public opinion to new portrayals of a group on television to the metrics guiding funding in a federal agency—presents unique challenges to scholars. Rather than treating culture as a social sphere separate from politics and the economy, we conceptualize it as the ideas, values, and assumptions underpinning policies and practices in all spheres. We review recent research on movements’ impacts on public opinion and everyday behavior; the media and popular culture; nonpolitical institutions such as science, medicine, and education; and politics. We focus on cultural impacts that have mattered for movements’ constituencies and address why movements have had those impacts. We conclude with an agenda for future research, seeking greater connection between the literatures on movements and the literatures on the institutions that matter to movements.

Online interaction is now a regular part of daily life for a demographically diverse population of hundreds of millions of people worldwide. These interactions generate fine-grained time-stamped records of human behavior and social interaction at the level of individual events, yet are global in scale, allowing researchers to address fundamental questions about social identity, status, conflict, cooperation, collective action, and diffusion, both by using observational data and by conducting in vivo field experiments. This unprecedented opportunity comes with a number of methodological challenges, including generalizing observations to the offline world, protecting individual privacy, and solving the logistical challenges posed by “big data” and web-based experiments. We review current advances in online social research and critically assess the theoretical and methodological opportunities and limitations.

The methodological tool chest available to those who study digital technologies ranges from those that are uniquely digital methods to approaches that are well established in the social sciences. This domain of work includes the application of methods to answer questions about the relationship between digital technologies and the social world, as well as the use of digital methods to answer questions about the offline world. New or old, quantitative or qualitative, the methods used to study the digital have strengths and weaknesses unique to this area of research. These issues include questions about the scope of cyberethnography, the validity of trace data, and the analytical division between on- and offline interaction. This review focuses on an overview of different methods, their history, and their strengths and weaknesses as applied to the study of digital technologies, including ethnographic approaches, interviews, surveys, time and media diaries, trace data, and online experiments.

Social life increasingly occurs in digital environments and continues to be mediated by digital systems. Big data represents the data being generated by the digitization of social life, which we break down into three domains: digital life, digital traces, and digitalized life. We argue that there is enormous potential in using big data to study a variety of phenomena that remain difficult to observe. However, there are some recurring vulnerabilities that should be addressed. We also outline the role institutions must play in clarifying the ethical rules of the road. Finally, we conclude by pointing to a number of nascent but important trends in the use of big data.

Despite recent and growing interest in using Twitter to examine human behavior and attitudes, there is still significant room for growth regarding the ability to leverage Twitter data for social science research. In particular, gleaning demographic information about Twitter users—a key component of much social science research—remains a challenge. This article develops an accurate and reliable data processing approach for social science researchers interested in using Twitter data to examine behaviors and attitudes, as well as the demographic characteristics of the populations expressing or engaging in them. Using information gathered from Twitter users who state an intention to not vote in the 2012 presidential election, we describe and evaluate a method for processing data to retrieve demographic information reported by users that is not encoded as text (e.g., details of images) and evaluate the reliability of these techniques. We end by assessing the challenges of this data collection strategy and discussing how large-scale social media data may benefit demographic researchers.

This article presents the first steps towards a sociological understanding of emergent social media. This article uses Twitter, the most popular social media website, as its focus. Recently, the social media site has been prominently associated with social movements in Libya, Egypt, Tunisia, and Algeria. Rather than rush to breathlessly describe its novel role in shaping contemporary social movements, this article takes a step back and considers Twitter in historical and broad sociological terms. This article is not intended to provide empirical evidence or a fully formed theoretical understanding of Twitter, but rather to provide a selected literature review and a set of directions for sociologists. The article makes connections specifically to Erving Goffman’s interactionist work, not only to make the claim that some existing sociological theory can be used to think critically about Twitter, but also to provide some initial thoughts on how such theoretical innovations can be developed.

This review examines studies of the affordances of digital technologies that produce virtuality. What we can call a “technological turn” in the literature considers technology a first-order analytical object rather than blackboxing it or subsuming it under social process. J.J. Gibson's original concept of affordance is explained, as well as its evolution to a concept consonant with anthropology's concerns. The review probes studies of political activism, work, and play. It comments on how virtuality affects anthropology as a discipline.

In this essay, we develop a framework for understanding the evolving relationships between technology, work, and family. We focus primarily on the temporal, spatial, and relational boundaries between work and family and the ways in which technology is changing boundary management practices. We suggest that the ubiquity and power of communications technologies require active technology management and, specifically, the development of a form of cultural capital that we call digital cultural capital. We are concerned that the technological changes currently underway may deepen and reinforce social and economic inequalities in new and unanticipated ways. We endeavor to synthesize and connect the disparate bodies of research on these nascent issues and lay out an agenda for future lines of inquiry.

he social integration of a city depends on the extent to which people from different neighborhoods have the opportunity to interact with one another, but most prior work has not developed formal ways of conceptualizing and measuring this kind of connectedness. In this article, we develop original, network-based measures of what we call “structural connectedness” based on the everyday travel of people across neighborhoods. Our principal index captures the extent to which residents in each neighborhood of a city travel to all other neighborhoods in equal proportion. Our secondary index captures the extent to which travels within a city are concentrated in a handful of receiving neighborhoods. We illustrate the value of our indices for the 50 largest American cities based on hundreds of millions of geotagged tweets over 18 months. We uncover important features of major American cities, including the extent to which their connectedness depends on a few neighborhood hubs, and the fact that in several cities, contact between some neighborhoods is all but nonexistent. We also show that cities with greater population densities, more cosmopolitanism, and less racial segregation have higher levels of structural connectedness. Our indices can be applied to data at any spatial scale, and our measures pave the way for more powerful and precise analyses of structural connectedness and its effects across a broad array of social phenomena.

The relationship between social networks and health encompasses everything from the flow of pathogens and information to the diffusion of beliefs and behaviors. This review addresses the vast and multidisciplinary literature that studies social networks as a structural determinant of health. In particular, we report on the current state of knowledge on how social contagion dynamics influence individual and collective health outcomes. We pay specific attention to research that leverages large-scale online data and social network experiments to empirically identify three broad classes of contagion processes: pathogenic diffusion, informational and belief diffusion, and behavioral diffusion. We conclude by identifying the need for more research on (a) how multiple contagions interact within the same social network, (b) how online social networks impact offline health, and (c) the effectiveness of social network interventions for improving population health.