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- W4281285896 abstract "During political campaigns, candidates use rhetoric to advance competing visions and assessments of their country. Research reveals that the moral language used in this rhetoric can significantly influence citizens’ political attitudes and behaviors; however, the moral language actually used in the rhetoric of elites during political campaigns remains understudied. Using a dataset of every tweet (N = 139,412) published by 39 U.S. presidential candidates during the 2016 and 2020 primary elections, we extracted moral language and constructed network models illustrating how candidates’ rhetoric is semantically connected. These network models yielded two key discoveries. First, we find that party affiliation clusters can be reconstructed solely based on the moral words used in candidates’ rhetoric. Within each party, popular moral values are expressed in highly similar ways, with Democrats emphasizing careful and just treatment of individuals and Republicans emphasizing in-group loyalty and respect for social hierarchies. Second, we illustrate the ways in which outsider candidates like Donald Trump can separate themselves during primaries by using moral rhetoric that differs from their parties’ common language. Our findings demonstrate the functional use of strategic moral rhetoric in a campaign context and show that unique methods of text network analysis are broadly applicable to the study of campaigns and social movements." @default.
- W4281285896 created "2022-05-24" @default.
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- W4281285896 date "2022-05-23" @default.
- W4281285896 modified "2023-10-03" @default.
- W4281285896 title "Mapping moral language on U.S. presidential primary campaigns reveals rhetorical networks of political division and unity" @default.
- W4281285896 doi "https://doi.org/10.31219/osf.io/wn5rx" @default.
- W4281285896 hasPublicationYear "2022" @default.
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