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Optimal multi-community network modularity for information diffusion

Author

Listed:
  • Jiaocan Wu

    (School of Computer and Information Technology, Henan Normal University, Xinxiang, Henan, China)

  • Ruping Du

    (School of Computer and Information Technology, Henan Normal University, Xinxiang, Henan, China)

  • YingYing Zheng

    (School of Computer and Information Technology, Henan Normal University, Xinxiang, Henan, China)

  • Dong Liu

    (School of Computer and Information Technology, Henan Normal University, Xinxiang, Henan, China)

Abstract

Studies demonstrate that community structure plays an important role in information spreading recently. In this paper, we investigate the impact of multi-community structure on information diffusion with linear threshold model. We utilize extended GN network that contains four communities and analyze dynamic behaviors of information that spreads on it. And we discover the optimal multi-community network modularity for information diffusion based on the social reinforcement. Results show that, within the appropriate range, multi-community structure will facilitate information diffusion instead of hindering it, which accords with the results derived from two-community network.

Suggested Citation

  • Jiaocan Wu & Ruping Du & YingYing Zheng & Dong Liu, 2016. "Optimal multi-community network modularity for information diffusion," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(08), pages 1-9, August.
    • Handle: RePEc:wsi:ijmpcx:v:27:y:2016:i:08:n:s0129183116500923
    DOI: 10.1142/S0129183116500923
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