A Parallel and Efficient Algorithm for Detecting Overlapping Communities in Social Networks

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Sabzekar Mostafa; Baradaran Nejad Shima; Khazaiepoor Mahdi; Kherad Mehdi

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Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR Year:2024 | Volume:22 | Issue:4 Page(s): 245-258

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Title

A Parallel and Efficient Algorithm for Detecting Overlapping Communities in Social Networks

Author(s)

Sabzekar Mostafa | Baradaran Nejad Shima | Khazaiepoor Mahdi | Kherad Mehdi | Issue Writer Certificate

Keywords

شبکه های اجتماعی

موازی سازی

کشف انجمن

انجمن های هم پوشان.

Abstract

Social networks are not only tools for communication but also represent one of the key potentials in business and commerce. One of the most significant issues in this field is clustering nodes and extracting effective and useful patterns from them, known as community detection. A major challenge in community detection within social networks is the vast number of nodes, which makes any kind of analysis difficult. Another challenge is the overlap of cluster members, referred to as overlapping communities. In such networks, each node may belong to multiple groups. Considering overlaps between communities—especially in large-scale networks—poses significant challenges in accurately detecting and identifying communities. Therefore, many studies tend to overlook this issue. In this paper, an approach is proposed to address these challenges. The most time-consuming step in the proposed algorithm, identifying influential nodes, is performed in parallel. Moreover, overlaps between communities are taken into account and analyzed. The results of evaluating the proposed method, in comparison with other existing methods, indicate its superiority in terms of the uniformity of the detected communities.

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