Abstract

ABSTRACT Given the sizable viewership of the U.S. presidential debates and the importance of moral sentiments in human behavior, this present investigation examined the relationship between moral framing in the U.S. presidential debates and the changes of moral words and self-transcendent emotions in tweets. For each presidential debate in 2016, we collected tweets on the day of the debate and the day after the debate. A total of 991,835 tweets were coded using the “bag-of-words” approach and supervised machine learning. The results showed that Clinton’s moral framing during the 2016 presidential debates was generally associated with harm/care and fairness in the tweets, whereas Trump’s moral framing was associated with ingroup loyalty and authority in the tweets. Interrupted time series analyses indicated that the effects of the debates on the moral words and self-transcendent emotions in the tweets were limited. Political candidates should aim to induce and then sustain moral sentiments in voters.

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