Social network analysis in college choice.
This research paper employs Social Network Analysis to examine the effect of peer groups on the college application process, taking Baylor University as a case study. Degree centrality and eigenvector centrality are two centrality measures used as interested independent variables. Findings reveal that peer groups have significant effects on college choice in terms of high school and home neighborhood networks. Specifically, a one standard deviation increase in degree centrality implies about a 1.5% rise in application rates, which means highly connected students with a higher degree centrality are more likely to apply to Baylor University. This paper indicates that Baylor University has attracted applicants who are clustered by ZIP Codes, showing that if a student lives or studies in an area where lots of peers are also identified by Baylor University as potential recruits, he or she will be more likely to apply to Baylor. Thus, our study helps to broaden strategies for college recruitment by exploring the important role of social networks.