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Link Prediction on Social Networks Based on Centrality Measures

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Principles of Social Networking

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 246))

Abstract

In order to understand and compare different social networks, the role of nodes, edges, and their relative importance needs to be investigated. The importance measures of nodes and edges within networks are useful for many social network analysis tasks and are known as centrality measures. These centrality measures allow analysts to investigate network structure, identify influential users, predict future connections, and perform many other related tasks. This chapter presents a study of centrality measures to predict future links in the network. We also choose four different metrics of Recall, Precision, AUPR, and AUC and evaluate the performance of different centrality measures corresponding to the link prediction problem on real-world social networks.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Bennett University, Greater Noida, India

    Shashank Sheshar Singh

  2. Department of Computer Science & Engineering, Indian Institute of Technology (BHU), Varanasi, 221 005, India

    Shivansh Mishra, Ajay Kumar & Bhaskar Biswas

Authors
  1. Shashank Sheshar Singh
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  2. Shivansh Mishra
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  3. Ajay Kumar
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  4. Bhaskar Biswas
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Corresponding author

Correspondence to Shivansh Mishra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Silchar, Cachar, Assam, India

    Anupam Biswas

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India

    Ripon Patgiri

  3. Department of Computer Science and Engineering, Indian Institute of Technology (BHU), Varanasi, India

    Bhaskar Biswas

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Singh, S.S., Mishra, S., Kumar, A., Biswas, B. (2022). Link Prediction on Social Networks Based on Centrality Measures. In: Biswas, A., Patgiri, R., Biswas, B. (eds) Principles of Social Networking. Smart Innovation, Systems and Technologies, vol 246. Springer, Singapore. https://doi.org/10.1007/978-981-16-3398-0_4

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  • DOI: https://doi.org/10.1007/978-981-16-3398-0_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3397-3

  • Online ISBN: 978-981-16-3398-0

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