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An information dissemination model based on positive and negative interference in social networks

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  • Ran, Maojie
  • Chen, Jiancu

Abstract

Considering that information dissemination in social networks will be affected by external factors, this paper proposes a new PaNSEIR (positive and negative susceptible exposed ignorant removal) model. The model first introduces the information interference function to describe the influence of external information. Then combines the complex network theory and the propagation dynamics theory to establish a dynamic equation of information propagation. Finally, the model is applied to Twitter and Sina Microblog for simulation and compared with the traditional SEIR model. The simulation results demonstrate that external information interference will greatly promote the dissemination of the original information. The comparison with the SEIR model shows that the PaNSEIR model can better reflect the characteristics of information dissemination in real social networks, proving that the proposed information dissemination model is both reasonable and effective. This model is helpful in understanding the spread of information in social networks and provides ideas for studying the impact of external interference on the spread of information in social networks in the future.

Suggested Citation

  • Ran, Maojie & Chen, Jiancu, 2021. "An information dissemination model based on positive and negative interference in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
  • Handle: RePEc:eee:phsmap:v:572:y:2021:i:c:s0378437121001874
    DOI: 10.1016/j.physa.2021.125915
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    References listed on IDEAS

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    Cited by:

    1. Jia He & Miao Ma & Yuxuan Zhou & Miaoke Wang, 2023. "What We Have Learned about the Characteristics and Differences of Disaster Information Behavior in Social Media—A Case Study of the 7.20 Henan Heavy Rain Flood Disaster," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    2. Ping Yu & Zhiping Wang & Yanan Sun & Peiwen Wang, 2022. "Risk Diffusion and Control under Uncertain Information Based on Hypernetwork," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    3. Jia Wang & Zhiping Wang & Ping Yu & Peiwen Wang, 2022. "The SEIR Dynamic Evolutionary Model with Markov Chains in Hyper Networks," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    4. Ping Yu & Peiwen Wang & Zhiping Wang & Jia Wang, 2022. "Supply Chain Risk Diffusion Model Considering Multi-Factor Influences under Hypernetwork Vision," Sustainability, MDPI, vol. 14(14), pages 1-15, July.

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