Homophily-based Community Formation in Social Networks using Fuzzy Logic and Decision-Making

Social networks have become integral to modern life, significantly influencing friendship formation and interpersonal interactions. This study focuses on homophily, which means people tend to connect with others who share similar interests. Homophily plays a key role in forming and shaping communities. The proposed methodology introduces an approach that integrates fuzzy logic and decision-making to discuss a framework for formation of homophily in user networks. Pairwise similarity scores are calculated using a user-interest matrix and the Jaccard index, while fuzzy logic categorizes these scores into levels like low, medium, and high. Decision-making thresholds are applied to form communities and assign users based on aggregated homophily scores. This method helps analyze how social networks are structured and suggests ways to create new connections within communities.