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An Overview on Reducing Social Networks’ Size

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Advanced Data Mining and Applications (ADMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13725))

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Abstract

Social networks are important dissemination platforms that allow the interchange of ideas. Such networks are omnipresent in our everyday life due to the explosive use of smartphones. Consequently, modern social networks have reached a significant number of users, making their size huge. Thereby scaling over such large data remains a challenging task. Reducing social networks’ size is a key task in social network analysis to deal with this data complexity. Many approaches have been developed in this direction. This paper is dedicated to proposing a new taxonomy covering different state-of-the-art methods designed to cope with the explosive growth of social network data. The suggested solution to the extensive generated data is to reduce the network’s size. We then categorized existing works into two main classes that reflect how the reduced network is generated. After that, we present new directions for reducing large-scale social network size.

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Notes

  1. 1.

    https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/.

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Authors and Affiliations

  1. MARS Research Lab LR17ES05 Higher Institute of Computer Science and Telecom (ISITCom), University of Sousse, Sousse, Tunisia

    Myriam Jaouadi & Lotfi Ben Romdhane

Authors
  1. Myriam Jaouadi
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  2. Lotfi Ben Romdhane
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Corresponding author

Correspondence to Myriam Jaouadi .

Editor information

Editors and Affiliations

  1. The University of Adelaide, Adelaide, SA, Australia

    Weitong Chen

  2. The University of New South Wales, Sydney, NSW, Australia

    Lina Yao

  3. Macquarie University, Sydney, NSW, Australia

    Taotao Cai

  4. Griffith University, Brisbane, QLD, Australia

    Shirui Pan

  5. Microsoft, Beijing, China

    Tao Shen

  6. The University of Queensland, Brisbane, QLD, Australia

    Xue Li

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Jaouadi, M., Ben Romdhane, L. (2022). An Overview on Reducing Social Networks’ Size. In: Chen, W., Yao, L., Cai, T., Pan, S., Shen, T., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2022. Lecture Notes in Computer Science(), vol 13725. Springer, Cham. https://doi.org/10.1007/978-3-031-22064-7_12

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  • DOI: https://doi.org/10.1007/978-3-031-22064-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22063-0

  • Online ISBN: 978-3-031-22064-7

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