Suchergebnisse

For most of the twentieth century, public opinion was nearly analogous with polling. Enter social media, which has upended the social, technical, and communication contingencies upon which public opinion is constructed. This study documents how political professionals turn to social media to understand the public, charting important implications for the practice of campaigning as well as the study of public opinion itself. An analysis of in-depth interviews with 13 professionals from 2016 US presidential campaigns details how they use social media to understand and represent public opinion. I map these uses of social media onto a theoretical model, accounting for quantitative and qualitative measurement, for instrumental and symbolic purposes. Campaigns' use of social media data to infer and symbolize public opinion is a new development in the relationship between campaigns and supporters. These new tools and symbols of public opinion are shaped by campaigns and drive press coverage (McGregor 2019), highlighting the hybrid logic of the political media system (Chadwick 2017). The model I present brings much-needed attention to qualitative data, a novel aspect of social media in understanding public opinion. The use of social media data to understand the public, for all its problems of representativeness, may provide a retort to long-standing criticisms of surveys—specifically that surveys do not reveal hierarchical, social, or public aspects of opinion formation (Blumer 1948; Herbst 1998; Cramer 2016). This model highlights a need to explicate what can—and cannot—be understood about public opinion via social media.

Scholars have documented growth in media coverage and popular discourse focusing on politicians' personal lives— personalization. Candidates use social media and personalization to circumvent mainstream news media, disrupting conventional processes. This personalization arguably increases voters' reliance on personal characteristics as voting heuristics. An online experiment exposed more than a thousand US adults to personalized or policy/campaigning tweets from a male or female US Senator running for re-election. Candidates who personalized elicited higher evaluations of social presence and parasocial interaction. For female candidates who shared a supported party with a respondent, personalization leads to feelings of perceived presence and parasocial interaction. Ultimately, the feelings of intimacy created by personalized tweets led respondents to express support for personalizing candidates, but this effect is contingent upon the gender and in-party status of the candidate.

Scholars increasingly point to polarization as a central threat to democracy—and identify technology platforms as key contributors to polarization. In contrast, we argue that polarization can only be seen as a central threat to democracy if inequality is ignored. The central theoretical claim of this piece is that political identities map more or less onto social groups, and groups are, in turn, located in social structures. As such, scholars must analyze groups as they are embedded in relations of power to meaningfully evaluate the democratic consequences of polarization. Groups struggling for equality, such as the Black Lives Matter movement, often cause polarization because they threaten the extant power and status of dominant groups. To develop a shared theoretical lens around polarization and its relationship with inequality, we take up the case of research on the role of platforms in polarization, showing how scholarship routinely lacks analysis of inequality.

"Big data raise major research possibilities for political communication scholars interested in how citizens, elites, and journalists interact. With the availability of social media data, academics can observe, on a large scale, how people talk about politics. The opportunity to study political discussions also is available to media organizations and political elites; examining how they make use of big data represents another fruitful scholarly trajectory. The scholars involved in Digital Discussions represent forward thinkers who aim to inform the study of political communication by analyzing the behavior of and messages left by citizens, elites, and journalists in digital spaces. Using a variety of methodological approaches and bringing diverse theoretical perspectives, this group sheds light on how big data can inform political communication research. It is critical reading for those studying and working in communication studies with a focus on big data"--

Abstract
This study explores frequency of election-related chatter as an antecedent to agenda setting. In this study, we conducted a longitudinal analysis of 38 million tweets from the 2012 election. Users who participate more in election talk align more with partisan media than less active users. Users who participate less align less with partisan media and more with mainstream media. Overall, agenda-setting relationships differ by participation in election-related talk, with more active users exhibiting a greater agenda-setting effect across all media types. This study provides evidence that as Twitter users talk more about the election, they appear to do so in more homophilous information environments. These environments can alter their perceived importance of issues to match more partisan media. This study echoes previous research that has shown large conversations on Twitter to be more akin to partisan information.