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Revisiting The American Voter on Twitter
- Source :
- CHI
- Publication Year :
- 2017
- Publisher :
- ACM, 2017.
-
Abstract
- The American Voter - a seminal work in political science - uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme - Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls.
- Subjects :
- Presidential system
media_common.quotation_subject
Discourse analysis
05 social sciences
Sentiment analysis
02 engineering and technology
Democracy
0506 political science
Management
Politics
Foreign policy
Political economy
Political science
050602 political science & public administration
0202 electrical engineering, electronic engineering, information engineering
Voting behavior
020201 artificial intelligence & image processing
Social media
media_common
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
- Accession number :
- edsair.doi...........d6c3a085cb905f4858229a0dfcf3c4b0
- Full Text :
- https://doi.org/10.1145/3025453.3025543