3.8 Article

Mapping moral language on US presidential primary campaigns reveals rhetorical networks of political division and unity

期刊

PNAS NEXUS
卷 2, 期 6, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/pnasnexus/pgad189

关键词

moral language; political campaigns; moral foundations theory; network analysis; natural language processing

向作者/读者索取更多资源

Research investigates the influence of moral language used by political candidates during campaigns and finds that it significantly affects citizens' political attitudes and behaviors. However, little research has been done on the moral language used by elite individuals during political campaigns. Using a dataset of tweets from 39 US presidential candidates during the 2016 and 2020 primary elections, the study explores the semantic connections in candidates' rhetoric and makes two key discoveries. Firstly, party affiliation can be determined based on the moral words used in candidates' rhetoric, with Democrats emphasizing individual care and justice and Republicans emphasizing in-group loyalty and respect for social hierarchies. Secondly, outsider candidates like Donald Trump differentiate themselves by using moral rhetoric different from their parties' common language. The findings highlight the strategic use of moral rhetoric in campaigns and the broad applicability of text network analysis in studying campaigns and social movements.
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 data set of every tweet (N=139,412) published by 39 US 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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据