Abstract
This study investigates the impact of interpersonal connections on the academic success of students at The College of Wooster, utilizing graph theory and social network analysis. By analyzing survey data on student involvement in various college organizations, this research aims to determine how shared connections influence academic outcomes, particularly GPA. Exploratory data analysis, decision trees, and random forest models were employed in the thesis to identify key predictors of student success. The results indicate that students with stronger social networks, defined by involvement in multiple organizations and shared attributes with peers, exhibit improved academic performance. Network centrality measures such as degree and betweenness centrality were then used and found to correlate significantly with GPA outcomes. While the analysis suggests that a minimum of five shared attributes is necessary to establish a meaningful network connection, further investigation is required to refine this threshold. These findings from this thesis provide valuable insights for institutions seeking to enhance student success through fostering positive interpersonal connections.
Advisor
Bush, Michael
Department
Mathematics
Recommended Citation
Karmacharya, Aashika, "Graph Theory Application in Social Network Analysis: Modeling the Dynamics of Academic Success and Well-being in College Students" (2025). Senior Independent Study Theses. Paper 11397.
https://openworks.wooster.edu/independentstudy/11397
Publication Date
2025
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2025 Aashika Karmacharya