Article ID Journal Published Year Pages File Type
10154275 Discourse, Context & Media 2018 10 Pages PDF
Abstract
This study investigated Hillary Clinton's and Donald Trump's speeches during the 2016 presidential election to identify their sentiments and discourse themes and strategies by using machine-based methods, including computerized sentence-level sentiment analysis, structural topic modeling for themes, and word2vec exploration for thematic associations. The machine-based automatic analyses were also complemented by a qualitative examination of the speech data motivated by the top thematic terms identified by the automatic analyses. The results of the study revealed that Trump's speeches were significantly more negative than Clinton's. The results also provided evidence supporting many previous findings regarding Clinton's and Trump's discourse/rhetoric styles and major campaign themes produced by studies using different research methods. The results of this study might also help explain Trump's victory despite the significant more negative sentiment in his discourse.
Related Topics
Social Sciences and Humanities Arts and Humanities Language and Linguistics
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