Spotting Key Influencers in Event Participation using Social Network Analysis

Abstract—Event participation within educational and profes- sional institutions is frequently driven by peer influence rather than direct advertising. Identifying the individuals who drive this participation is crucial for optimizing outreach strategies. This paper proposes a Social Network Analysis (SNA) approach to identify key influencers in event participation networks. By constructing a directed graph where nodes represent participants and edges represent invitation relationships, we apply centrality metrics including PageRank, Betweenness Centrality, and Degree Centrality to compute influence scores. Furthermore, this study categorizes influence across three distinct domains: Student, Business, and Entertainment events. The system includes an interactive dashboard developed using Streamlit to visualize network structures and rank influencers. The results demonstrate that SNA provides a more accurate identification of influential individuals compared to traditional participation counts, offering actionable insights for data-driven event management. Index Terms—Social Network Analysis, Influencer Detection, PageRank, Centrality Measures, Community Detection, Event Management.