OVERLAPPING COMMUNITY DETECTION ALGORITHMS USING MODULARITY AND THE COSINE

Duy Hieu Do () and Thi Ha Duong Phan
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Duy Hieu Do: Institute of Mathematics, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Vietnam
Thi Ha Duong Phan: ��International Centre for Research and Postgraduate Training in Mathematics Under the Auspices of UNESCO, Institute of Mathematics, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet, Cau Giay, Ha Noi, Vienam

Advances in Complex Systems (ACS), 2025, vol. 28, issue 03, 1-28

Abstract: The issue of network community detection has been extensively studied across many fields. Most community detection methods assume that nodes belong to only one community. However, in many cases, nodes can belong to multiple communities simultaneously. This paper presents two overlapping network community detection algorithms that build on the two-step approach, using the extended modularity and cosine function. The applicability of our algorithms extends to both undirected and directed graph structures. To demonstrate the feasibility and effectiveness of these algorithms, we conducted experiments using real data.

Keywords: Overlapping community detection; directed graph; random walk; stationary distribution; cosine similarity (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0219525925500067

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