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Crossover phenomena in growth pattern of social contagions with restricted contact

Author

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  • Zhu, Yu-Xiao
  • Cao, Yan-Yan
  • Chen, Ting
  • Qiu, Xiao-Yan
  • Wang, Wei
  • Hou, Rui

Abstract

Considering the phenomenon that each individual has its limited contact capacity due to inelastic resources (i.e., time and energy), we propose one non-Markovian model to investigate the effects of contact capacity on social contagions, in which each adopted individual can only contact and transmit the information to certain number of neighbors. A heterogeneous edge-based compartmental approach is applied to analyze the social contagion on strongly heterogenous networks with skewed degree distribution, and the analytical results agree well with simulations. We find that either enlarging the contact capacity or decreasing adoption threshold makes the network more fragile to behavior spreading. Interestingly, we find that both the continuous and discontinuous dependence of the final adoption size on the effective information transmission probability can arise. There is a crossover phenomenon between the two types of dependence. More specifically, the crossover phenomenon can be induced by changing any one of certain parameters, i.e., the average degree, the fraction of initial seeds and adoption threshold.

Suggested Citation

  • Zhu, Yu-Xiao & Cao, Yan-Yan & Chen, Ting & Qiu, Xiao-Yan & Wang, Wei & Hou, Rui, 2018. "Crossover phenomena in growth pattern of social contagions with restricted contact," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 408-414.
    • Handle: RePEc:eee:chsofr:v:114:y:2018:i:c:p:408-414
    DOI: 10.1016/j.chaos.2018.06.010
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    References listed on IDEAS

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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Gao, Bo & Deng, Zhenghong & Zhao, Dawei, 2016. "Competing spreading processes and immunization in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 175-181.
    3. 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.
    4. Wu, Qingchu & Chen, Shufang & Zha, Lingling, 2017. "Epidemic spreading over quenched networks with local behavioral response," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 17-22.
    5. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, January.
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    Cited by:

    1. Li, Wenjie & Li, Jiachen & Nie, Yanyi & Lin, Tao & Chen, Yu & Liu, Xiaoyang & Su, Sheng & Wang, Wei, 2024. "Infectious disease spreading modeling and containing strategy in heterogeneous population," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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