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The Spreading of Information in Online Social Networks through Cellular Automata

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  • Yuda Wang
  • Gang Li

Abstract

Epidemic dynamics in complex networks have been extensively studied. Due to the similarity between information and disease spreading, most studies on information dynamics use epidemic models and merely consider the characteristics of online social networks and individual’s cognitive. In this paper, we propose an online social networks information spreading (OSIS) model combining epidemic models and individual’s cognitive psychology. Then we design a cellular automata (CA) method to provide a computational method for OSIS. Finally, we use OSIS and CA to simulate the spreading and evolution of information in online social networks. The experimental results indicate that OSIS is effective. Firstly, individual’s cognition affects online information spreading. When infection rate is low, it prevents the spreading, whereas when infection rate is sufficiently high, it promotes transmission. Secondly, the explosion of online social network scale and the convenience of we-media greatly increase the ability of information dissemination. Lastly, the demise of information is affected by both time and heat decay rather than probability. We believe that these findings are in the right direction for perceiving information spreading in online social networks and useful for public management policymakers seeking to design efficient programs.

Suggested Citation

  • Yuda Wang & Gang Li, 2018. "The Spreading of Information in Online Social Networks through Cellular Automata," Complexity, Hindawi, vol. 2018, pages 1-9, November.
    • Handle: RePEc:hin:complx:1890643
    DOI: 10.1155/2018/1890643
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    References listed on IDEAS

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    1. Wang, Wei & Chen, Xiao-Long & Zhong, Lin-Feng, 2018. "Social contagions with heterogeneous credibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 604-610.
    2. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    3. Henrique Gagliardi & Domingos Alves, 2010. "Small-World Effect in Epidemics Using Cellular Automata," Mathematical Population Studies, Taylor & Francis Journals, vol. 17(2), pages 79-90.
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    Cited by:

    1. Leonidas Sakalauskas & Vitalij Denisov & Aiste Dirzyte, 2023. "Hybrid Modeling of Anxiety Propagation in Response to Threat Stimuli Flow," Mathematics, MDPI, vol. 11(19), pages 1-20, September.

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