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Virtual Exhibit Hall
X (Twitter)
We develop a classification model to detect attacks in U.S. House members’ Tweets based on the text and contextual data such as political party. We apply this model to a novel dataset, assessing whether 1.25 million Tweets contain political attacks.
Nicholas I Deas, Clemson University
Jacob Sargent, Clemson University
Spencer A Shellnutt, Clemson University