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CSSI: Connected by Comments: The Evolving Affect Network of Presidential Candidates on Twitter During the 2016 GOP Nomination Contest

29 Jan
Friday, 01/29/2016 12:00pm to 2:00pm
Computer Science Building, Room 150/151
CSSI Lunch
Speaker: Justin Gross

"Connected by Comments: The Evolving Affect Network of Presidential Candidates on Twitter During the 2016 GOP Nomination Contest "

Abstract:  The unprecedented number of serious candidates in the Republican Party's 2016 nomination contest for the U.S. Presidency provides a rare opportunity to examine the changing nature of affective relationships among candidates. All seventeen major candidates have Twitter accounts and have tweeted comments about their opponents both before the campaigning began and over the course of the campaign for the GOP nomination. Political scientists, writing on the phenomenon of negative campaigning, have made a number predictions about what conditions will make it more likely that a campaign shall "go negative." These researchers have concentrated on advertisements, but the number and variety of advertisements produced are highly dependent on a campaign's resources. By contrast, candidates' use of social media allows us to directly observe, in real time, candidate interaction. Furthermore, the nature of "going negative" is more complicated in a crowded field and would seem to benefit from a network analytic approach. Structural balance theory, in particular, provides some guidance in thinking about the dynamics of positive and negative affect, operationalized as a signed network. However, peer group and organizational behavior, commonly driving theories of structural balance, are rather distinct from the behavior among electoral competitors. How likely is it that, in an environment tending toward mutual animosity, a taste for structural balance will somehow prevail? I address this question, examine clustering patterns, and describe some highlights of the online conflicts and collaborations that have played out this election season.

Bio:  Justin H. Gross is Assistant Professor of Political Science at UMass Amherst. He holds a Ph.D. in Statistics and Public Policy from Carnegie Mellon University. His applied research interests are in mass media and political communication, public opinion, and public policy. He works on methodological problems in measurement, text analysis, and network analysis, and is especially interested in methods that put statistical and computational tools to use in service of our ability to achieve rich qualitative insights. Recently, he has been collaborating with a cross-disciplinary team of political scientists and computational linguists, developing tools for the detection of issue frames and publicly expressed ideologies in text.

Lunch will be provided, beginning at 12:00
Talk begins at 12:30