Closeness centrality for networks with overlapping community structure

Mateusz K. Tarkowski, Piotr Szczepański, Talal Rahwan, Tomasz P. Michalak, Michael Wooldridge

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Certain real-life networks have a community structure in which communities overlap. For example, a typical bus network includes bus stops (nodes), which belong to one or more bus lines (communities) that often overlap. Clearly, it is important to take this information into account when measuring the centrality of a bus stop-how important it is to the functioning of the network. For example, if a certain stop becomes inaccessible, the impact will depend in part on the bus lines that visit it. However, existing centrality measures do not take such information into account. Our aim is to bridge this gap. We begin by developing a new game-Theoretic solution concept, which we call the Configuration semivalue, in order to have greater flexibility in modelling the community structure compared to previous solution concepts from cooperative game theory. We then use the new concept as a building block to construct the first extension of Closeness centrality to networks with community structure (overlapping or otherwise). Despite the computational complexity inherited from the Configuration semivalue, we show that the corresponding extension of Closeness centrality can be computed in polynomial time. We empirically evaluate this measure and our algorithm that computes it by analysing the Warsaw public transportation network.

    Original languageEnglish (US)
    Title of host publication30th AAAI Conference on Artificial Intelligence, AAAI 2016
    PublisherAAAI press
    Pages622-629
    Number of pages8
    ISBN (Electronic)9781577357605
    StatePublished - Jan 1 2016
    Event30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States
    Duration: Feb 12 2016Feb 17 2016

    Other

    Other30th AAAI Conference on Artificial Intelligence, AAAI 2016
    CountryUnited States
    CityPhoenix
    Period2/12/162/17/16

    Fingerprint

    Game theory
    Computational complexity
    Polynomials

    ASJC Scopus subject areas

    • Artificial Intelligence

    Cite this

    Tarkowski, M. K., Szczepański, P., Rahwan, T., Michalak, T. P., & Wooldridge, M. (2016). Closeness centrality for networks with overlapping community structure. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016 (pp. 622-629). AAAI press.

    Closeness centrality for networks with overlapping community structure. / Tarkowski, Mateusz K.; Szczepański, Piotr; Rahwan, Talal; Michalak, Tomasz P.; Wooldridge, Michael.

    30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, 2016. p. 622-629.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Tarkowski, MK, Szczepański, P, Rahwan, T, Michalak, TP & Wooldridge, M 2016, Closeness centrality for networks with overlapping community structure. in 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, pp. 622-629, 30th AAAI Conference on Artificial Intelligence, AAAI 2016, Phoenix, United States, 2/12/16.
    Tarkowski MK, Szczepański P, Rahwan T, Michalak TP, Wooldridge M. Closeness centrality for networks with overlapping community structure. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press. 2016. p. 622-629
    Tarkowski, Mateusz K. ; Szczepański, Piotr ; Rahwan, Talal ; Michalak, Tomasz P. ; Wooldridge, Michael. / Closeness centrality for networks with overlapping community structure. 30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, 2016. pp. 622-629
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