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Influence Clubs in Social Networks

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6422))

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Abstract

A new model “influence club” for cohesion group in a social network is proposed. It generalizes the definition of k-club and has two advantages. First, the influence between two nodes does not only depend on the their distance but also on the numbers of pathways of different lengths. Second, the new model is more flexible than k-club and can provide middle results between k-club and (k + 1)-club. We propose a branch-and-bound algorithm for finding the maximum influence club. For an n-node graph, the worst-case time complexity is O(n 3 1.6n), and it is much more efficient in practical: a graph of 200 nodes can be processed within 2 minutes. The performance compared to k-clubs are tested on random graphs and real data. The experimental results also show the advantages of the influence clubs.

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Author information

Authors and Affiliations

  1. National Chung Cheng University, ChiaYi, 621, Taiwan, R.O.C.

    Chin-Ping Yang, Chen-Yi Liu & Bang Ye Wu

Authors
  1. Chin-Ping Yang
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  2. Chen-Yi Liu
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  3. Bang Ye Wu
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Yang, CP., Liu, CY., Wu, B.Y. (2010). Influence Clubs in Social Networks. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_1

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  • DOI: https://doi.org/10.1007/978-3-642-16732-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16731-7

  • Online ISBN: 978-3-642-16732-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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