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A Novel Architecture for Community Detection Between Large Social Media Creators

Publication Type : Journal Article

Publisher : Elsevier

Source : Procedia Computer Science

Url : https://www.sciencedirect.com/science/article/pii/S187705092400557X

Campus : Amritapuri

School : School of Computing

Year : 2024

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

Cite this Research Publication : Swain, Dhruvjyoti, S. Eesha, Gokul D. Raj, and T. Anjali. "A Novel Architecture for Community Detection Between Large Social Media Creators." Procedia Computer Science 233 (2024): 87-96.

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