Publication

Abstract : Social Network Analysis (SNA) plays a vital role in comprehending the structure, behavior, and development of online communities through the identification of influential nodes, community detection, and interaction pattern analysis. It facilitates applications in recommendation systems, targeted marketing, and information diffusion, and hence is critical for digital communication and engagement strategy optimization. Subreddit networks, community structures, and influential nodes have been analysed through this paper for the prediction of future interactions. Complex community detection algorithms were used for identifying modular communities, and centrality metrics were used for the quantification of node influence within the network. Temporal dynamics analysis was conducted to monitor com munity and network structure evolution over time.Ensemble machine learning models were used to make predictions of link formation, making use of centrality and interaction patterns to increase prediction accuracy.The model was tested with major performance indicators to determine its predictive ability. The findings of this research provide much insight into community behavior, centrality of central nodes, and the effect of Ensemble model efficiency in link prediction. Ensemble models of link prediction can provide a more efficient extension of social network understanding to cater to applications in recommendation systems, community management, and marketing strategy.