3 research outputs found
The Structure of U.S. College Networks on Facebook
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.Comment: ICWSM-202