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A Community-Aware Approach to Minimizing Dissemination in Graphs

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 10366)

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.

Keywords

  • Dissemination control in graph
  • Community structure
  • Graph mining

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Notes

  1. 1.

    We use the following similar terms in this paper: graph and network, vertex and node, edge and link.

  2. 2.

    Most of our datasets are available at https://snap.stanford.edu/data/.

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Acknowledgements

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).

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Correspondence to Zi-Ke Zhang or Tao Zhou .

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Zhang, C., Yu, L., Liu, C., Zhang, ZK., Zhou, T. (2017). A Community-Aware Approach to Minimizing Dissemination in Graphs. In: Chen, L., Jensen, C., Shahabi, C., Yang, X., Lian, X. (eds) Web and Big Data. APWeb-WAIM 2017. Lecture Notes in Computer Science(), vol 10366. Springer, Cham. https://doi.org/10.1007/978-3-319-63579-8_8

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  • DOI: https://doi.org/10.1007/978-3-319-63579-8_8

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