Model, Analyze, and Comprehend User Interactions within a Social Media Platform

• URL: http://arxiv.org/abs/2403.15937v2
• Date: Thu, 28 Nov 2024 05:29:32 GMT
• Title: Model, Analyze, and Comprehend User Interactions within a Social Media Platform
• Authors: Md Kaykobad Reza, S M Maksudul Alam, Yiran Luo, Youzhe Liu, Md Siam,
• Abstract summary: We construct a user interaction graph from social media data and analyze it to gain insights into community dynamics. Our study provides a comprehensive framework for understanding and managing online communities.
• Score: 0.6990493129893112
• License:
• Abstract: In this study, we propose a novel graph-based approach to model, analyze and comprehend user interactions within a social media platform based on post-comment relationship. We construct a user interaction graph from social media data and analyze it to gain insights into community dynamics, user behavior, and content preferences. Our investigation reveals that while 56.05% of the active users are strongly connected within the community, only 0.8% of them significantly contribute to its dynamics. Moreover, we observe temporal variations in community activity, with certain periods experiencing heightened engagement. Additionally, our findings highlight a correlation between user activity and popularity showing that more active users are generally more popular. Alongside these, a preference for positive and informative content is also observed where 82.41% users preferred positive and informative content. Overall, our study provides a comprehensive framework for understanding and managing online communities, leveraging graph-based techniques to gain valuable insights into user behavior and community dynamics.

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