Predicting Viewer Reactions to Discourse in Political Debates

نویسنده

  • Peter Enns
چکیده

It is increasingly common for researchers in the humanities and social sciences make use of computational analysis of large datasets to answer research questions. One field where computational analysis is getting traction is political science. In this paper, we leverage a particularly rich dataset from the domain of political science that contains the transcript of one of the 2012 presidential debates and finegrained reactions from viewers over the course of the debate. This dataset allows us to investigate the effectiveness of tools from natural language processing for answering interesting research questions about the debate. In particular, we attempt to predict viewer reactions to utterances from both candidates. We weigh the benefits and drawbacks of several competing approaches and explore some potential improvements.

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تاریخ انتشار 2014