Journalists are constructing public opinion when they use social media accounts to tell the story of politics
Public opinion, as necessary a concept it is to the underpinnings of democracy, is a socially constructed representation of the public that is forged by the methods and data from which it is derived, as well as how it is understood by those tasked with evaluating and utilizing it. I examine how social media manifests as public opinion in the news and how these practices shape journalistic routines. I draw from a content analysis of news stories about the 2016 US election, as well as interviews with journalists, to shed light on evolving practices that inform the use of social media to represent public opinion. I find that despite social media users not reflecting the electorate, the press reported online sentiments and trends as a form of public opinion that services the horserace narrative and complements survey polling and vox populi quotes. These practices are woven into professional routines – journalists looked to social media to reflect public opinion, especially in the wake of media events like debates. Journalists worried about an overreliance on social media to inform coverage, especially Dataminr alerts and journalists’ own highly curated Twitter feeds. Hybrid flows of information between journalists, campaigns, and social media companies inform conceptions of public opinion.
The more expensive and competitive the election, the more Twitter will talk about it
In recent years, journalists, political elites, and the public have used Twitter as an indicator of political trends. Given this usage, what effect do campaign activities have on Twitter discourse? What effect does that discourse have on electoral outcomes? We posit that Twitter can be understood as a tool for and an object of political communication, especially during elections. This study positions Twitter volume as an outcome of other electoral antecedents and then assesses its relevance in election campaigns. Using a data set of more than 3 million tweets about 2014 U.S. Senate candidates from three distinct groups—news media, political actors, and the public—we find that competitiveness and money spent in the race were the main predictors of volume of Twitter discourse, and the impact of competitiveness of the race was stronger for tweets coming from the media when compared to the other groups. Twitter volume did not predict vote share for any of the 35 races studied. Our findings suggest that Twitter is better understood as a tool for political communication, and its usage may be predicted by money spent and race characteristics. As an object, Twitter use has limited power to predict electoral outcomes.
People are more interested in women candidates when they're running against men
As campaign discussions increasingly circulate within social media, it is important to understand the characteristics of these conversations. Specifically, we ask whether well-documented patterns of gendered bias against women candidates persist in socially networked political discussions. Theorizing power dynamics as relational, we use dialectic configurations between actors as independent variables determining network measures as outcomes. Our goal is to assess relational power granted to candidates through Twitter conversations about them and whether they change depending on the gender of their opponent. Based on more than a quarter of a million tweets about 50 candidates for state-wide offices during the 2014 US elections, results suggest that when a woman opposes a man, the conversation revolves around her, but she retains a smaller portion of rhetorical share. We find that gender affects network structure—women candidates are both more central and more replied to when they run against men. Despite the potential for social media to disrupt deeply rooted gender bias, our findings suggest that the structure of networked discussions about male and female candidates still results in a differential distribution of relational power.