No abstract

“Media events” generate conditions of shared attention as many users simultaneously tune in with the dual screens of broadcast and social media to view and participate. We examine how collective patterns of user behavior under conditions of shared attention are distinct from other “bursts” of activity like breaking news events. Using 290 million tweets from a panel of 193,532 politically active Twitter users, we compare features of their behavior during eight major events during the 2012 U.S. presidential election to examine how patterns of social media use change during these media events compared to “typical” time and whether these changes are attributable to shifts in the behavior of the population as a whole or shifts from particular segments such as elites. Compared to baseline time periods, our findings reveal that media events not only generate large volumes of tweets, but they are also associated with (1) substantial declines in interpersonal communication, (2) more highly concentrated attention by replying to and retweeting particular users, and (3) elite users predominantly benefiting from this attention. These findings empirically demonstrate how bursts of activity on Twitter during media events significantly alter underlying social processes of interpersonal communication and social interaction. Because the behavior of large populations within socio-technical systems can change so dramatically, our findings suggest the need for further research about how social media responses to media events can be used to support collective sensemaking, to promote informed deliberation, and to remain resilient in the face of misinformation.

Communication and other → social networks have been the subject of considerable scholarship since the eighteenth century (Mattelart 2000), but the past two decades have produced unprecedented growth in network theorizing and research. Further, this interest in communication and information networks now spans the social sciences, including sociology, psychology, history, political science, organization science, and economics, as well as the physical and life sciences. As Castells (2000) has so comprehensively elucidated, we are now living in the age of the network society.

Organizational communities are typically defined as populations of organizations that are tied together by networks of communication and other relations in overlapping resource niches. Traditionally, evolutionary theorists and researchers have examined organizational populations that comprise organizational communities by focusing on their properties rather than on the networks that link them. However, a full understanding of the evolution of organizational communities requires insight into both organizations and their networks. Consequently, this article presents a variety of conceptual tools for applying evolutionary theory to organizations, organizational communities, and their networks, including the notions of relational carrying capacity and linkage fitness. It illustrates evolutionary principles, such as variation, selection, and retention, that lead to the formation, growth, maintenance, and eventual demise of communication and other network linkages. This perspective allows us to understand the ways in which community survival and success are as dependent on their communication linkages as they are on the organizations they connect. The article concludes with suggestions for potential applications of evolutionary theory to other areas of human communication.networks is used to demonstrate new conceptualizations that can be derived from an evolutionary perspective. These include a community ecology approach to organizational linkages, the concept of relational carrying capacity, and the variation, selection, and retention (V-S-R) of network links.Organizational communities are typically defined as ''a spatially or functionally bounded set of populations'' of organizations that are tied together by networks of communication and other relations in overlapping resource niches (Aldrich & Ruef, 2006, p. 240). Traditionally, evolutionary theorists and researchers have examined organizational populations that comprise organizational communities. This article extends the application of evolutionary theory to community and population communication networks. It focuses on evolutionary principles, including V-S-R, that lead to the formation, growth, maintenance, and eventual demise of network linkages. This perspective allows us to understand the ways in which community survival and success are as dependent on communication and other organizational linkages as they are on the organizations these linkages connect.Evolutionary theory has a number of advantages over more traditional approaches to the study of networks of organizations. First, the community ecology perspective examines the evolution of organizational populations and the communities in which they exist. This shifts attention away from single, individual organizations toward populations of organizations and their relations with other organizational entities (Aldrich, 1999). Second, community ecology explores the role of environmental resource niches and organizational adaptation, seeing these as fundamental driving forces in the maintenance of communitie...

Risk research has theorized a number of mechanisms that might trigger, prolong, or potentially alleviate individuals' distress following terrorist attacks. These mechanisms are difficult to examine in a single study, however, because the social conditions of terrorist attacks are difficult to simulate in laboratory experiments and appropriate preattack baselines are difficult to establish with surveys. To address this challenge, we propose the use of computational focus groups and a novel analysis framework to analyze a social media stream that archives user history and location. The approach uses time-stamped behavior to quantify an individual's preattack behavior after an attack has occurred, enabling the assessment of time-specific changes in the intensity and duration of an individual's distress, as well as the assessment of individual and social-level covariates. To exemplify the methodology, we collected over 18 million tweets from 15,509 users located in Paris on November 13, 2015, and measured the degree to which they expressed anxiety, anger, and sadness after the attacks. The analysis resulted in findings that would be difficult to observe through other methods, such as that news media exposure had competing, time-dependent effects on anxiety, and that gender dynamics are complicated by baseline behavior. Opportunities for integrating computational focus group analysis with traditional methods are discussed.