Detecting Overlapping Communities in Complex Networks: A New Strategy

Authors

  • Bashar Mohammed Tuama, Laith Ali Abdulsahib

Keywords:

Community detection, Network analysis, Overlapping community discovery (OCD), Clique Percolation Method (CPM), Graph theory.

Abstract

Conventional community identification techniques concentrate on communities that do not overlap and to which each node only belongs once. Many real-world networks, however, exhibit nested community structures, allowing nodes to take part in numerous communities at once. The identification of these overlapping communities is crucial for comprehending the intricate structure and dynamic behavior of these networks.

The suggested method employs a local similarity metric to identify each node's prospective community membership. To compute the local similarities, it considers the nodes' close neighbors as well as their structural characteristics. Additionally, a global optimization process is used to enhance the communities by taking into account the links and overall network design.

After overlapping communities are found, the procedure probably aims to examine their traits and connections. This might entail analyzing community structure over time, finding important nodes or connections between communities, and investigating patterns of node interconnection. To glean insights from the discovered communities, several network evaluation metrics and visualization instruments might be used.Therefore, this research offers a potential method for identifying nesting communities within complex connections, which may have applications in a number of areas, including social network evaluation and data retrieval.

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Published

2024-02-28

How to Cite

Bashar Mohammed Tuama, Laith Ali Abdulsahib. (2024). Detecting Overlapping Communities in Complex Networks: A New Strategy. Utilitas Mathematica, 120, 1330–1344. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/1886

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