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Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks

Author

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  • Sen Pei
  • Shaoting Tang
  • Zhiming Zheng

Abstract

Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans’ physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks), we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods.

Suggested Citation

  • Sen Pei & Shaoting Tang & Zhiming Zheng, 2015. "Detecting the Influence of Spreading in Social Networks with Excitable Sensor Networks," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-19, May.
  • Handle: RePEc:plo:pone00:0124848
    DOI: 10.1371/journal.pone.0124848
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    References listed on IDEAS

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    1. Wang, Jia-zeng & Liu, Zeng-rong & Xu, Jianhua, 2007. "Epidemic spreading on uncorrelated heterogenous networks with non-uniform transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 715-721.
    2. Yan, Shu & Tang, Shaoting & Pei, Sen & Jiang, Shijin & Zhang, Xiao & Ding, Wenrui & Zheng, Zhiming, 2013. "The spreading of opposite opinions on online social networks with authoritative nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3846-3855.
    3. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
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