Measuring and Unpacking Affective Polarization on Twitter: The Role of Party and Gender in the 2018 Senate Races
affective polarization; twitter; liberal; conservative; politics; gender; voting; out-group party sentiment; data analytics; machine learning for social media
Hawaii International Conference on System Sciences
Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/
This study examines how the Twittersphere talked about candidates running for the U.S senate in the 2018 congressional elections. We classify Twitter users as Liberal or Conservative to better understand how the two groups use social media during a major national political election. Using tweet sentiment, we assess how the Twittersphere felt about in-group party versus out-group party candidates. When we further break these findings down based on the candidates’ gender, we find that male senatorial candidates were talked about more positively than female candidates. We also find that Conservatives talked more positively about female Republican candidates than they did about Republican male candidates. Female candidates of the out-group party were talked about the least favorably of all candidates. Conservative tweeters exhibit the most positive level of in-group party sentiment and the most negative level of out-group party sentiment. We therefore attribute the most intense affective polarization to this ideological group.
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