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    User ratings analysis in social networks through a hypernetwork method

    Access Status
    Fulltext not available
    Authors
    Suo, Q.
    Sun, S.
    Hajli, N.
    Love, Peter
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Suo, Q. and Sun, S. and Hajli, N. and Love, P. 2015. User ratings analysis in social networks through a hypernetwork method. Expert Systems with Applications. 42 (21): pp. 7317-7325.
    Source Title
    Expert Systems with Applications
    DOI
    10.1016/j.eswa.2015.05.054
    ISSN
    0957-4174
    School
    Department of Civil Engineering
    URI
    http://hdl.handle.net/20.500.11937/26060
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 Elsevier B.V. All rights reserved. This study utilizes the critical properties of a complex social network to reveal its intrinsic characteristics and the laws governing the way information propagates across the network to identify the central, active users and opinion leaders. The hypernetwork method is applied to analyze user ratings in social networks (SNSs). After introducing the concept of a hypernetwork and its topological characteristics such as node degree, the strength of the node and node hyperdegree, collaborative recommendations in hypernetworks are formulated based on the topological characteristics. Finally, the new method developed is applied to analyze data from the Douban social network. In this hypernetwork, users are defined as hyperedges and the objects as nodes. Three hypernetworks focused on reviews of books, movies and music were constructed using the proposed method and found to share a similar law of trends. These topological characteristics are clearly an effective way to reflect the relationship between users and objects. This research will enable SNSs providers to offer better object resource management and a personalized service for users, as well as contributing to empirical analyses of other similar SNSs.

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