Abstract

Many networks of interest to Information Systems researchers exhibit community structure. This macro-scale structure is so natural that community detection is an essential task to divide large networked data sets into manageable groups to enable an understanding of a system at the meso-scale. In the present work, we aim at introducing this elegant approach as the state-of the-art knowledge to the IS research community, manage to extent the method to multi-edge networks, and apply successfully the extended method to a real-world school best friendship context.

Editor: H. Kemal İlter, Ankara Yıldırım Beyazıt University, Turkey
Received: August 19, 2018, Accepted: October 18, 2018, Published: November 10, 2018

Copyright: © 2018 IMISC Perdahcı et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.