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Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction
António Fonseca1, Catarina Pontes1, Sérgio Moro1,2
1Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Lisbon, Portugal.
Heliyon
|June 13, 2024
Summary
This study on Twitter/X Portuguese networks reveals that users who follow more accounts are more likely to post aggressive content. Hate speech often occurs early in conversations and is typically introduced by external users.
Area of Science:
- Social Media Analysis
- Computational Social Science
- Network Science
Background:
- Hate speech is a significant problem on social media platforms like Twitter/X.
- Understanding the dynamics of hate speech in Portuguese-language conversations is crucial.
Purpose of the Study:
- To analyze the characteristics and patterns of hate speech in the Twitter/X Portuguese network.
- To identify factors predicting the occurrence and nature of hate speech.
Main Methods:
- Mixed-method approach combining network analysis (triad census, participation shifts) and qualitative content annotation.
- Analysis of user interaction networks within the Twitter/X Portuguese community.
Main Results:
- The number of followed users predicts a user's propensity for aggressive content.
- Hate speech is more prevalent within the first 2 hours of conversation threads.
- Hate speech reduces interaction transitivity and individual expression.
- External users are the primary source of direct hate speech intrusions.
- Indirect hate speech by third parties is uncommon.
- Counter-speech is associated with non-confrontational, public discourse.
Conclusions:
- User network size and early interaction dynamics influence hate speech prevalence.
- Hate speech disrupts conversational flow and expression.
- External intrusion is a key pattern, while indirect interference is rare.
- Counter-speech operates differently from typical conflict-avoidant discourse.
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