The Structure of U.S. College Networks on Facebook

TL;DR

This paper presents a large-scale dataset of U.S. college social networks from Facebook, introduces a new methodology for comparing networks of different sizes, and reveals patterns related to school type and cohort similarity.

Contribution

It provides the first comprehensive dataset linking Facebook social networks with college data and develops a novel method for comparing networks across diverse institutions.

Findings

Networks of the same school across cohorts are more similar than across different schools.

Public/private and graduation rate are key factors in network structure differences.

Private school students tend to have larger, more clustered, and more homophilous networks.

Abstract

Anecdotally, social connections made in university have life-long impact. Yet knowledge of social networks formed in college remains episodic, due in large part to the difficulty and expense involved in collecting a suitable dataset for comprehensive analysis. To advance and systematize insight into college social networks, we describe a dataset of the largest online social network platform used by college students in the United States. We combine de-identified and aggregated Facebook data with College Scorecard data, campus-level information provided by U.S. Department of Education, to produce a dataset covering the 2008-2015 entry year cohorts for 1,159 U.S. colleges and universities, spanning 7.6 million students. To perform the difficult task of comparing these networks of different sizes we develop a new methodology. We compute features over sampled ego-graphs, train binary classifiers for every pair of graphs, and operationalize distance between graphs as predictive accuracy. Social networks of different year cohorts at the same school are structurally more similar to one another than to cohorts at other schools. Networks from similar schools have similar structures, with the public/private and graduation rate dimensions being the most distinguishable. We also relate school types to specific outcomes. For example, students at private schools have larger networks that are more clustered and with higher homophily by year. Our findings may help illuminate the role that colleges play in shaping social networks which partly persist throughout people's lives.