Comparative study of kinship network community detection approaches

Abstract

This study employs five community detection methods on a rooted tree network with 600 nodes and 599 edges based on the Galo tribe’s kin naming system in Arunachal Pradesh, India. The network was originally assumed to be made up of three communities, which the algorithms were able to further divide into smaller groupings. The Louvain approach produced the most balanced distribution of community sizes, with skewness and kurtosis values close to zero, implying that the detected communities were reasonably evenly distributed in size and without major outliers. However, the Louvain algorithm found 25 communities, which is more than the network’s previously reported three communities. Further investigation may be required to integrate some of these communities in order to obtain the original known communities. Overall, this study highlights the importance of selecting an appropriate community detection algorithm for a given network and research question.