A Novel Architecture for Community Detection Between Large Social Media Creators

Abstract

This study explores the intricate web of audience overlap among streamers on live streaming platforms. The extensive growth of streaming services has led to a proliferation of individual streamers. A comprehensive understanding of the audience overlap network between these streamers offers valuable insights into user behavior and preferences, presenting unique opportunities for collaboration. This research introduces a novel methodology, leveraging network analysis techniques, to map out the overlap network among individual streamers. The methodology applies advanced principles of overlap detection and community identification within social networks, resulting in an effective approach for discerning overlapping viewer communities. This study has significant implications for enhancing user engagement and collaboration among streamers, as well as improving the effectiveness of recommendations, benefiting streaming platforms, advertisers, and content creators alike