A methodology and theoretical taxonomy for centrality measures

In social network analysis several measures were developed to assess a nodes’ centrality in a graph. Among these measures, we find connectivity or degree-based measures, geodesic distance-based indices, geodesic path-based scores and centrality measures related to a node’s neighborhood. Most studies dedicated to student networks use degree, closeness and/or betweenness centralities, even if other measures might be valid candidates for representing and understanding these networks. We choose eighteen centrality measures and computed these measures on a student network. The data were collected at Saint-Louis University in Brussels (i.e., USL-B), Belgium, in October 2016 A total of 574 first-generation freshmen students (students registered in their first year of studies for the first time) completed a paper survey. They were asked about their friendship ties at university. Since the survey was not mandatory, students who did not participate could nevertheless be cited as ties. We imputed the friendship relations for those 296 missing actors. This imputation enabled us to compute centrality measures for the 574 respondents and also for each of the 870 students belonging to the augmented network, that is, the 574 respondents and the 296 missing actors to whom ties were imputed. <br><br><br><br><br><br><br><br>