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Incremental methods for community detection in both fully and growing dynamic networks Cover

Incremental methods for community detection in both fully and growing dynamic networks

Open Access
|Feb 2022

Abstract

In recent years, community detection in dynamic networks has received great interest. Due to its importance, many surveys have been suggested. In these surveys, the authors present and detail a number of methods that identify a community without taking into account the incremental methods which, in turn, also take an important place in dynamic community detection methods. In this survey, we provide a review of incremental approaches to community detection in both fully and growing dynamic networks. To do this, we have classified the methods according to the type of network. For each type of network, we describe three main approaches: the first one is based on modularity optimization; the second is based on density; finally, the third is based on label propagation. For each method, we list the studies available in the literature and state their drawbacks and advantages.

Language: English
Page range: 220 - 250
Submitted on: Jun 2, 2021
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Accepted on: Oct 19, 2021
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Published on: Feb 2, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2022 Fariza Bouhatem, Ali Ait El Hadj, Fatiha Souam, Abdelhakim Dafeur, published by Sapientia Hungarian University of Transylvania
This work is licensed under the Creative Commons Attribution 4.0 License.