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    A Community-Aware Approach to Minimizing Dissemination in Graphs

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    Type
    Conference Paper
    Authors
    Zhang, Chuxu
    Yu, Lu
    Liu, Chuang
    Zhang, Zi-Ke
    Zhou, Tao
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Date
    2017-08-03
    Online Publication Date
    2017-08-03
    Print Publication Date
    2017
    Permanent link to this record
    http://hdl.handle.net/10754/626774
    
    Metadata
    Show full item record
    Abstract
    Given a graph, can we minimize the spread of an entity (such as a meme or a virus) while maintaining the graph’s community structure (defined as groups of nodes with denser intra-connectivity than inter-connectivity)? At first glance, these two objectives seem at odds with each other. To minimize dissemination, nodes or links are often deleted to reduce the graph’s connectivity. These deletions can (and often do) destroy the graph’s community structure, which is an important construct in real-world settings (e.g., communities promote trust among their members). We utilize rewiring of links to achieve both objectives. Examples of rewiring in real life are prevalent, such as purchasing products from a new farm since the local farm has signs of mad cow disease; getting information from a new source after a disaster since your usual source is no longer available, etc. Our community-aware approach, called constrCRlink (short for Constraint Community Relink), preserves (on average) 98.6% of the efficacy of the best community-agnostic link-deletion approach (namely, NetMelt+), but changes the original community structure of the graph by only 4.5%. In contrast, NetMelt+ changes 13.6% of the original community structure.
    Citation
    Zhang C, Yu L, Liu C, Zhang Z-K, Zhou T (2017) A Community-Aware Approach to Minimizing Dissemination in Graphs. Lecture Notes in Computer Science: 85–99. Available: http://dx.doi.org/10.1007/978-3-319-63579-8_8.
    Sponsors
    This work was partially supported by Natural Science Foundation of China (Grant Nos. 61673151, 61503110 and 61433014), Zhejiang Provincial Natural Science Foundation of China (Grant Nos. LY14A050001 and LQ16F030006).
    Publisher
    Springer Nature
    Journal
    Lecture Notes in Computer Science
    Conference/Event name
    1st Asia-Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2017
    DOI
    10.1007/978-3-319-63579-8_8
    Additional Links
    https://link.springer.com/chapter/10.1007%2F978-3-319-63579-8_8
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-319-63579-8_8
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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