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Interlocking Nodes for Structural Analysis in Social Networking

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Advanced Computing and Communication Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 702))

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Abstract

In this work, an algorithm for detecting the interlocking nodes in the temporal networks has been proposed. Interlocking nodes are set of nodes joining together in same set of networks. These nodes make change in the structural changes of the temporal network. Different techniques exist in the literature to identify structural changes of the temporal network. Structural changes are essential elements for identifying patterns and events in temporal social networks. A method for finding structural changes and the events related to communities is presented in the paper. These events can be used for pattern detection in networks with evolving communities.

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Acknowledgements

The author is grateful to Securities and Exchange Board of India (SEBI) for providing the data set containing lists of Indian companies and other information required for the implementation of the algorithm.

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Authors and Affiliations

  1. Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad, 500078, India

    S. A. S. Bommakanti

Authors
  1. S. A. S. Bommakanti
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Correspondence to S. A. S. Bommakanti .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Faculty of Engineering, Technology and Management, University of Kalyani, Kalyani, West Bengal, India

    Jyotsna Kumar Mandal

  2. Computational Science Division, Saha Institute of Nuclear Physics, Kolkata, West Bengal, India

    Dhananjay Bhattacharyya

  3. Department of Computer Science and Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, India

    Nitin Auluck

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Bommakanti, S.A.S. (2019). Interlocking Nodes for Structural Analysis in Social Networking. In: Mandal, J., Bhattacharyya, D., Auluck, N. (eds) Advanced Computing and Communication Technologies. Advances in Intelligent Systems and Computing, vol 702. Springer, Singapore. https://doi.org/10.1007/978-981-13-0680-8_6

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