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The impact of group propagation on rumor spreading in mobile social networks

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  • Sahafizadeh, Ebrahim
  • Tork Ladani, Behrouz

Abstract

A group in a mobile social network is normally considered as a particular contact in which invited individuals can share messages. People in a mobile social network sometimes share rumor messages with the contacts in the group that are not necessarily familiar with them. They normally get the rumor messages posted by different users and forward them to the other individuals or groups. There are some models for analysis of rumor propagation in mobile social networks. However, none of them have considered the concept of rumor propagation into groups of nodes. In this paper we study the rumor spreading in mobile social networks when the concept of group propagation is also considered. For this purpose, we extend the SIR information propagation model and investigate the impact of group propagation on the dynamics of rumor spreading process. We conduct steady-state analysis to investigate the basic reproduction number of the rumor spreading in the model. Furthermore, agent-based modeling and simulation is used to analyze the final size of the rumor under various group propagation rates as well as the impacts of group parameters on group spreading dynamics. The simulation results obtained by Monte Carlo method show that group propagation effectively increases the rumor spreading speed. We show that having large groups is more effective on rumor spreading than having more groups. Furthermore we analyze the influence of network structure on rumor spreading when group propagation is considered. For this purpose, two Erdős–Rényi and Barabási–Albert models of social networks are considered and it is shown that rumor spreading behavior in these networks have no significant differences when we have rumor propagation in groups.

Suggested Citation

  • Sahafizadeh, Ebrahim & Tork Ladani, Behrouz, 2018. "The impact of group propagation on rumor spreading in mobile social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 412-423.
    • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:412-423
    DOI: 10.1016/j.physa.2018.04.038
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    References listed on IDEAS

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    Cited by:

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    8. Dmitry Zhukov & Julia Perova & Vladimir Kalinin, 2022. "Description of the Distribution Law and Non-Linear Dynamics of Growth of Comments Number in News and Blogs Based on the Fokker-Planck Equation," Mathematics, MDPI, vol. 10(6), pages 1-24, March.
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