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Gender dynamics on Twitter during the 2020 U.S. Democratic presidential primary
Catherine King1, Kathleen M Carley1
1Software and Societal Systems Department, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213 USA.
Social Network Analysis and Mining
|March 20, 2023
Summary
Analysis of 2020 Democratic presidential candidates on Twitter revealed that while top candidates received more engagement and bot attacks, female candidates faced more gendered and sexist language, indicating persistent stereotypes in social media discourse.
Area of Science:
- Social Media Analysis
- Political Science
- Computational Social Science
Background:
- The 2020 U.S. Democratic presidential primary featured intense social media engagement.
- Understanding online discourse is crucial for analyzing political campaigns.
Purpose of the Study:
- To investigate differences in how top U.S. Democratic presidential candidates were treated on Twitter during the 2020 primary.
- To identify patterns of engagement, bot activity, and abusive language directed at candidates.
Main Methods:
- Analysis of Twitter data for the top five U.S. Democratic presidential candidates.
- Data collection spanned December 2019 to April 2020.
- Categorization of discussions and user interactions per candidate.
Main Results:
- The most discussed candidates (Biden, Sanders) garnered the most engagement from verified users and news agencies.
- These popular candidates also faced higher targeting from bots and trolls.
- Female candidates (Warren, Klobuchar) experienced more gendered and sexist language in abusive mentions.
- Sexist slurs targeting women were more prevalent than male slurs across all datasets.
Conclusions:
- Social media conversations surrounding female presidential candidates may still reflect underlying sexist stereotypes.
- The nature of online attacks differs based on candidate popularity and gender.
- Further research is needed to fully understand the impact of gendered online abuse in politics.
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