Analyzing Social Media Engagement of Computer Science Conferences

TL;DR

The study analyzes 22 computer science conference accounts on X over a 14-year span to understand how follower count, engagement, content categories, sentiment, and post length shape online presence. By combining a Nitter-based data collection (10,187 posts), a statistically representative manual sample (352 posts), and multiple tests (Chi-Square, Kruskal-Wallis, Pearson correlation), the authors reveal that follower count correlates with some engagement metrics but does not universally predict interaction, and that content and sentiment vary significantly across conferences. The findings show that likes are the dominant engagement mode, and that certain content themes (e.g., Awards, Community Events) drive high interaction; these insights can help conferences tailor social media strategies. The work also highlights methodological considerations for researching social media in academia and points to future cross-platform analyses to capture a broader picture of online conference participation.

Abstract

Context: X, formerly known as Twitter, is one of the largest social media platforms and has been widely used for communication during research conferences. While previous studies have examined how users engage with X during these events, limited research has focused on analyzing the content posted by computer science conferences. Objective: This study investigates how conferences from different areas of computer science perform on social media by analyzing their activity, follower engagement, and the content posted on X. Method: We collect posts from 22 computer science conferences and conduct statistical experiments to identify variations in content. Additionally, we perform a manual analysis of the top five posts for each engagement metric. Results: Our findings indicate statistically significant differences in category, sentiment, and post length across computer science conference posts. Among all engagement metrics, likes were the most common way users interacted with conference content. Conclusion: This study provides insights into the social media presence of computer science conferences, highlighting key differences in content, sentiment, and engagement patterns across different venues.

Figures (5)

• Figure 1: Conferences' X-Post Length
• Figure 2: User Likes on Conferences' Posts on X
• Figure 3: User Reposts on Conferences' Posts on X
• Figure 4: User Shares on Conferences' Posts on X
• Figure 5: User Replies on Conferences' Posts on X