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Fractional STIR Epidemic Model for Opinion Dissemination in Social Networks

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 88))

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Abstract

Social networking services (SNS) have become the main channels for public opinion due to their large users, highly connected interactivity and the immediacy of dissemination. Therefore, it is of great theoretical and practical significance to study the transmission mechanism of Internet public opinion and master the law of public opinion transmission. Based on the traditional SIR epidemic model, this paper introduces Thoughtful (T), a new node that receives transmitted information but considers whether to spread. It also considers the dynamic process of some immunizers becoming communicators and derivative effects. In this paper, a fractional STIR model is proposed, which is based on conformable derivatives and the STIR model. By implementing the MATLAB simulation, the experimental results show that the fractional STIR model has a high degree of fit of the actual data with a small error. Therefore, our model can effectively describe the dynamic process of the evolution of Internet public opinion.

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Author information

Authors and Affiliations

  1. School of Science, Xi’an University of Post and Telecommunications, Xi’an, 710121, China

    Qiujuan Tong & Jianke Zhang

  2. School of Electronics and Communication Engineering, Xi’an University of Post and Telecommunications, Xi’an, 710121, China

    Ruining Dong

  3. School of Modern Post, Xi’an University of Post and Telecommunications, Xi’an, 710121, China

    Xiaobao Yang

Authors
  1. Qiujuan Tong
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  2. Ruining Dong
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  3. Jianke Zhang
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  4. Xiaobao Yang
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Editor information

Editors and Affiliations

  1. College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK

    Hongying Meng

  2. School of Electronical Information and Artificial Engineering, Shaanxi University of Science and Technology, Xi’an, China

    Tao Lei

  3. College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK

    Maozhen Li

  4. College of Electrical and Information, Hunan University, Changsha, China

    Kenli Li

  5. Division of Intelligent Future Technologies, Mälardalen University, Västerås, Västmanlands Län, Sweden

    Ning Xiong

  6. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Lipo Wang

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Tong, Q., Dong, R., Zhang, J., Yang, X. (2021). Fractional STIR Epidemic Model for Opinion Dissemination in Social Networks. In: Meng, H., Lei, T., Li, M., Li, K., Xiong, N., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 88. Springer, Cham. https://doi.org/10.1007/978-3-030-70665-4_17

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