Predicting Stability of Community Members in Complex Networks
Social and Information Networks
2022-07-14 v3 Discrete Mathematics
Physics and Society
Abstract
In this work, we analyse and predict the stability of communities in complex networks. We use a variant of closeness centrality, known as profile closeness, to measure the loyalty of a member towards its community. We show that the profile closeness is an adequate indicator of how communities evolve in a network. We investigate this in static as well as dynamic (temporal) networks and establish the relevance of profile closeness in predicting the evolution of a complex network. Keywords: Small world networks , Centrality , Community , Closeness , Clustering
Cite
@article{arxiv.1903.06232,
title = {Predicting Stability of Community Members in Complex Networks},
author = {Sruthi K S and Divya Sindhu Lekha and A Sreekumar and Kannan Balakrishnan},
journal= {arXiv preprint arXiv:1903.06232},
year = {2022}
}