Analyzing Peer Influence in a Network of College Students by Kayla Chang & James Murray ’25

Abstract: The intensely social nature of college networks can play a crucial role in influencing student behavior. This talk introduces network analysis as a tool for studying interpersonal relationships and highlights a study examining peer influence on substance use and exercise among college students. Using community detection methods such as the Girvan-Newman Algorithm, as well as Network Autocorrelation Modeling, we identify social clusters within the network and quantify behavioral influence within groups. The findings offer insight into how peer dynamics reinforce or discourage health-related behaviors.