On the relationship between the structural and socioacademic communities of a coauthorship network

• Published in: Journal of informetrics 2008-07, Vol.2 (3), p.195-201
• Main Authors: Rodriguez, Marko A., Pepe, Alberto
• Format: Article
• Language: English
• Subjects: Collaboration patterns; Community detection; Social networks; Structures and organization in human complex systems
• ISSN: 1751-1577; 1875-5879
• DOI: 10.1016/j.joi.2008.04.002

This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic record of a multi-institution, interdisciplinary research group focused on the study of sensor networks and wireless communication. Four different community detection algorithms were employed to assign a structural community to each scholar in the network: leading eigenvector, walktrap, edge betweenness and spinglass. Socioacademic characteristics were gathered from the scholars and include such information as their academic department, academic affiliation, country of origin, and academic position. A Pearson’s χ 2 test, with a simulated Monte Carlo, revealed that structural communities best represent groupings of individuals working in the same academic department and at the same institution. A generalization of this result suggests that, even in interdisciplinary, multi-institutional research groups, coauthorship is primarily driven by departmental and institutional affiliation.