Graph Neural Networks for Social Network Analysis and Community Detection

Abstract

Understanding complex relationships in social networks requires advanced modeling techniques. This paper explores the use of Graph Neural Networks (GNNs) for community detection and link prediction. By capturing structural and relational information, the proposed model identifies hidden patterns within large-scale networks. Experimental evaluation on benchmark datasets demonstrates improved accuracy and scalability compared to traditional graph-based methods.