Complex Network Analysis Approach to Examining Undergraduate Program Preferences

Abstract

In this study, we analyzed undergraduate program preferences of students by using complex network analysis techniques. We collected program preferences data from the YokAtlas portal provided by the Council of Higher Education using a web crawler we developed. We constructed a kind of co-occurrence network we called copreference network of 622 nodes and 6,136 edges from the collected raw data. We performed a comprehensive exploratory complex network analysis on the co-preference network using Cytoscape and NodeXL tools. Using several node centrality measures, we identified the most popular programs that students frequently preferred together with other programs. In addition, we observed the clusters of programs embedded in the network using several network community detection methods. Finally, we performed a structure analysis to compare our network to a corresponding random network, and we showed that our network had the common characteristic properties that many real-world networks exhibit.