Community Structure in Online Collegiate Social Networks

We apply the tools of network analysis to study the roles of university organizations and affiliations in structuring the social networks of students by examining the graphs of Facebook “friendships” at five American universities at a single point in time. In particular, we investigate each single-institution network’s community structure, which we obtain by partitioning the graphs using an eigenvector method. We employ both graphical and quantitative tools, including pair-counting methods that we interpret through statistical analysis and permutation tests, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We additionally investigate single-gender subsets of the university networks and also examine the impact of incomplete demographic information in the data. Our study across five universities allows one to make comparative observations about the online social lives at the different institutions, which can in turn be used to infer differences in offline lives. It also illustrates how to examine different instances of social networks constructed in similar environments, while emphasizing the array of social forces that combine to form simplified “communities” obtainable by the consideration of the friendship links. In an appendix, we review the basic properties and statistics of the employed paircounting similarity coefficients and recall, in simplified notation, a useful analytical formula for the z-score of the Rand coefficient.