Optimal multi-community network modularity for information diffusion

Jiaocan Wu, Ruping Du, YingYing Zheng and Dong Liu ()
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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

International Journal of Modern Physics C (IJMPC), 2016, vol. 27, issue 08, 1-9

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.

Keywords: Complex network; community structure; optimal modularity threshold (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1142/S0129183116500923

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