Community detection plays a central role in the analysis of social networks, where individuals naturally form structured groups such as neighborhood clusters or small rural communities. A key challenge in this domain is accurately identifying these communities—commonly defined as subsets of nodes that are more densely connected internally than with the rest of the network. Traditional methods often rely on hierarchical clustering for this task. However, recent research has explored alternative approaches involving various clustering strategies and connectivity-based evaluation metrics. In this study, we introduce a novel method called the Biggest Degree Head Node Technique (BDNHT) and evaluate its effectiveness against the conventional Random Head Node Technique. The proposed method focuses on selecting an optimal set of centroids using fitness-based criteria, aiming to achieve more meaningful and well-separated community structures.
Keywords
Network Node, Clustering, Biggest Degree Head, Social Networks, Longest Distance Head, Social Community, Cluster.
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CRediT Author Statement
The authors confirm contribution to the paper as follows:
Conceptualization:Amedapu Srinivas and Leela Velusamy;
Methodology: Amedapu Srinivas;
Software: Leela Velusamy;
Data Curation: Amedapu Srinivas;
Writing- Original Draft Preparation: Amedapu Srinivas and Leela Velusamy;
Visualization: Amedapu Srinivas;
Investigation: Leela Velusamy;
Supervision: Amedapu Srinivas;
Validation: Leela Velusamy;
Writing- Reviewing and Editing: Amedapu Srinivas and Leela Velusamy;All authors reviewed the results and approved the final version of the manuscript.
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Author(s) thanks to Dr.Leela Velusamy for this research completion and support.
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Amedapu Srinivas
Department of Computer Science and Engineering, NIT Trichy, National Institute of Technology, Tamil Nadu, India.
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Cite this article
Amedapu Srinivas and Leela Velusamy, “Community Detection Algorithm Based on High Degree Node Selection in Complex Networks”, Journal of Machine and Computing, vol.5, no.3, pp. 1864-1872, July 2025, doi: 10.53759/7669/jmc202505146.
