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September 10, 2025Engineering Technology & Applied Science ResearchOpen Access

An Iterated Heuristic Community Detection Algorithm for Social Networks Based on Centrality and Similarity Measures

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Authors

ACAli ChenaouiMTMohammed Amin Tahraoui

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Overview

Heuristic algorithm shows improved community detection in social networks, indicating benefits of centrality and similarity measures.

Key Points

  • The iterative heuristic algorithm effectively identifies communities in social networks, enhancing understanding of network structures.
  • Local and global structural information is incorporated, showing improved accuracy in community detection with the proposed method.
  • Centrality and similarity measures are crucial for selecting leader nodes and forming communities based on quantified relationships.
  • Experiments on real networks demonstrate the robustness and effectiveness of the community detection approach presented.

Cite This Study

Chenaoui et al. (2025) studied this question.

synapsesocial.com/papers/68c1ac0954b1d3bfb60e4972https://doi.org/10.48084/etasr.10791
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