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Information spreading in complex networks with participation of independent spreaders

Author

Listed:
  • Ma, Kun
  • Li, Weihua
  • Guo, Quantong
  • Zheng, Xiaoqi
  • Zheng, Zhiming
  • Gao, Chao
  • Tang, Shaoting

Abstract

Information diffusion dynamics in complex networks is often modeled as a contagion process among neighbors which is analogous to epidemic diffusion. The attention of previous literature is mainly focused on epidemic diffusion within one network, which, however neglects the possible interactions between nodes beyond the underlying network. The disease can be transmitted to other nodes by other means without following the links in the focal network. Here we account for this phenomenon by introducing the independent spreaders in a susceptible–infectious–recovered contagion process. We derive the critical epidemic thresholds on Erdős–Rényi and scale-free networks as a function of infectious rate, recovery rate and the activeness of independent spreaders. We also present simulation results on ER and SF networks, as well as on a real-world email network. The result shows that the extent to which a disease can infect might be more far-reaching, than we can explain in terms of link contagion only. Besides, these results also help to explain how activeness of independent spreaders can affect the diffusion process, which can be used to explore many other dynamical processes.

Suggested Citation

  • Ma, Kun & Li, Weihua & Guo, Quantong & Zheng, Xiaoqi & Zheng, Zhiming & Gao, Chao & Tang, Shaoting, 2018. "Information spreading in complex networks with participation of independent spreaders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 21-27.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:21-27
    DOI: 10.1016/j.physa.2017.09.052
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    Cited by:

    1. Jia, Pingqi & Wang, Chao & Zhang, Gaoyu & Ma, Jianfeng, 2019. "A rumor spreading model based on two propagation channels in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 342-353.
    2. Yanqiao Zheng & Xiaobing Zhao & Xiaoqi Zhang & Xinyue Ye & Qiwen Dai, 2019. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network," Complexity, Hindawi, vol. 2019, pages 1-17, May.

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