Comparing Community Structure to Characteristics in Online Collegiate Social Networks
Amanda L. Traud, Eric D. Kelsic, Peter J. Mucha, and Mason A. Porter

TL;DR
This study analyzes Facebook friendship networks at five US universities to understand how student characteristics influence community formation, revealing multiple factors contribute to social structures online and offline.
Contribution
It introduces a methodology combining graphical and quantitative tools to compare community structures and their correlations with student attributes across different universities.
Findings
Community structures are influenced by multiple student characteristics.
Common high school affiliation significantly impacts community formation.
Different universities show varying influences of characteristics like major and high school.
Abstract
We study the structure of social networks of students by examining the graphs of Facebook "friendships" at five American universities at a single point in time. We investigate each single-institution network's community structure and employ graphical and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the pair-counting indices employed and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form "communities," and leads to comparative observations about…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
