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Centrality Measures in Finding Influential Nodes for the Big-Data Network

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Handbook of Smart Materials, Technologies, and Devices

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Abstract

Network analysis determines node-to-node connectivity and examines each node’s features. Various tools are available in the literature to study networks like graph theoretical, statistical, and many. As the graph plays a vital role in representing networks, the centrality measurements play an essential role in network analysis. The centrality measures use various metrics for evaluating how important the node is. The centrality predicts the characteristics and importance of the nodes in the network. In this review, selected 16 centrality measures presented along with their implementations.

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Acknowledgments

The authors thank the Department of Science and Technology – Fund for improvement of S & T Infrastructure in Universities and Higher Educational Institutions, Government of India (SR/FST/MSI-107/2015) and the second author wishes to express sincere thanks to the INSPIRE fellowship (DST/INSPIRE Fellowship/2019/IF190271) for their financial support.

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Authors and Affiliations

  1. Department of Mathematics, School of Arts, Science, Humanities and Education, SASTRA Deemed to be University, Thanjavur, India

    Sathyanarayanan Gopalakrishnan, Supriya Sridharan & Swaminathan Venkatraman

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  1. Sathyanarayanan Gopalakrishnan
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  2. Supriya Sridharan
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  3. Swaminathan Venkatraman
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Editors and Affiliations

  1. Department of Chemistry and Environmental Science, New Jersey Institute of Technology, Newark, NJ, USA

    Chaudhery Mustansar Hussain

  2. School of Science, University of Padova, Padova, Italy

    Paolo Di Sia

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Gopalakrishnan, S., Sridharan, S., Venkatraman, S. (2022). Centrality Measures in Finding Influential Nodes for the Big-Data Network. In: Hussain, C.M., Di Sia, P. (eds) Handbook of Smart Materials, Technologies, and Devices. Springer, Cham. https://doi.org/10.1007/978-3-030-84205-5_103

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