Beyond Fact-Checking: Lexical Patterns as Lie Detectors in Donald Trump’s Tweets

Authors

  • Dorian Hunter Davis Webster University
  • Aram Sinnreich American University

Keywords:

Donald Trump, fact-checking, journalism, lying, Twitter, truth-default theory

Abstract

Journalists often debate whether to call Donald Trump’s falsehoods “lies” or stop short of implying intent. This article proposes an empirical tool to supplement traditional fact-checking methods and address the practical challenge of identifying lies. Analyzing Trump’s tweets with a regression function designed to predict true and false claims based on their language and composition, it finds significant evidence of intent underlying most of Trump’s false claims, and makes the case for calling them lies when that outcome agrees with the results of traditional fact-checking procedures.

Author Biographies

Dorian Hunter Davis, Webster University

Assistant Professor of Media Studies

Aram Sinnreich, American University

Associate Professor of Communication

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Published

2020-09-29

Issue

Vol. 14 (2020)

Section

Articles

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