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Model Construction and Empirical Research on Cross-Platform Propagation of Disinformation

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Advanced Intelligent Computing Technology and Applications (ICIC 2024)

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Abstract

Based on the prevalence and complexity of disinformation propagation on current social networks, this research aims to explore the propagation principles of cross-platform disinformation and construct a corresponding propagation model. First, we collected a typical disinformation topic on Weibo and analyzed the propagation characteristics of the topic. Then, a two-layer coupled social network model was constructed based on a positively correlated coupling strategy of node weights. Finally, we proposed a disinformation propagation model for coupled social networks, referred to as the CSN_SIR model. The CSN_SIR model integrates the classic framework of the SIR model with the coupling characteristics of social networks, enabling more accurate simulation and prediction of the disinformation propagation process. To validate the effectiveness of the model, we reconstructed the propagation graph of disinformation on Weibo and conducted simulation experiments of the model. The experimental results indicate that the CSN_SIR model can effectively replicate the propagation trends of disinformation. In addition, this study reveals the key features of disinformation propagation when spreading across platforms, providing new perspectives for understanding disinformation propagation in cross-platform social networks.

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References

  1. CNNIC. https://www.cnnic.net.cn/n4/2024/0322/c88-10964.html. Accessed 8 Apr 2024

  2. Wang, J., Wang, Y., Huang, M.J.: False information in social networks: definition, detection and control. Comput. Sci. 48(08), 263–277 (2021)

    Google Scholar 

  3. Dhar, J., Jain, A., Gupta, V.K.: A mathematical model of news propagation on online social network and a control strategy for rumor spreading. Soc. Netw. Anal. Min. 6, 1–9 (2016)

    Google Scholar 

  4. Wang, X., Ni, W., Zheng, K., Liu, R.P., Niu, X.: Virus propagation modeling and convergence analysis in large-scale networks. IEEE Trans. Inf. Forensics Secur. 11(10), 2241–2254 (2016)

    Article  Google Scholar 

  5. Schimit, P.H., Pereira, F.H.: Disease spreading in complex networks: a numerical study with principal component analysis. Expert Syst. Appl. 97, 41–50 (2018)

    Article  Google Scholar 

  6. Cheng, Y., Liu, C., Ding, F., et al.: Dynamic analysis of rumor spreading model for considering active network nodes and nonlinear spreading rate. Physica A 506, 24–35 (2018)

    Article  MathSciNet  Google Scholar 

  7. Sahafizadeh, E., Ladani, B.T.: The impact of group propagation on rumor spreading in mobile social networks. Physica A 506, 412–423 (2018)

    Article  MathSciNet  Google Scholar 

  8. Tian, Y., Ding, X.: Rumor spreading model with considering debunking behavior in emergencies. Appl. Math. Comput. 363, 124599 (2019)

    MathSciNet  Google Scholar 

  9. Hengmin, Z., Liu, Y., Jin, M., Jing, W.: Study on public opinion propagation model based on coupled networks under online to offline interaction. J. Intell. 35(2), 7 (2016)

    Google Scholar 

  10. Li Dandan, M.J.: Public opinion spreading dynamics in a two-layer social network. Syst. Eng. Theory Pract. 37(10), 2672–2679 (2017)

    Google Scholar 

  11. Zhang, L., Su, C., Jin, Y., Goh, M., Wu, Z.: Cross-network dissemination model of public opinion in coupled networks. Inf. Sci. 451, 240–252 (2018)

    Article  MathSciNet  Google Scholar 

  12. Jing, W., Yangjianghao, H., Hengming, Z.: Research on public opinion communication model of social network based on coupling network. J. Mod. Inf. 39(10), 9 (2019)

    Google Scholar 

  13. Li Gang, W.Y.: Research on rumor dissemination model based on audience portrait under age coupled social networks. J. Mod. Inf. 40(1), 12 (2020)

    Google Scholar 

  14. Jiang, C., Zhang, Y., Wang, H., Zhou, Y., Zou, Y.: Study on coupled social network public opinion communication based on improved SEIR. In: ISPA/BD Cloud/Social Com/Sustain Com, pp. 1495–1500. IEEE (2020)

    Google Scholar 

  15. Luo, Z., Pei, Z., Xiong, W., Liu, M.: Research on dynamics of information spreading on double-layer coupled networks. Comput. Simul. 40(01), 43–47 (2023)

    Google Scholar 

  16. Zhang, Z., Jing, J., Li, F., Zhao, C.: Survey on fake information detection, propagation and control in online social networks from the perspective of artificial intelligence. Chin. J. Comput. 44(11), 2261–2282 (2021)

    Google Scholar 

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Acknowledgement

This research was supported by the Guangxi Key Research and Development Funding (2019AB35004; AB20238030), the National Natural Science Foundation of China (No. 62062014), the grant from Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips (No. BCIC-23-Z1), and the Key Scientific Research Project of Guangxi Normal University (No. 2018ZD007).

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Correspondence to Ming Jiang or Fuyun He .

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Chen, J., Jiang, M., He, F. (2024). Model Construction and Empirical Research on Cross-Platform Propagation of Disinformation. In: Huang, DS., Chen, W., Guo, J. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2024. Lecture Notes in Computer Science, vol 14870. Springer, Singapore. https://doi.org/10.1007/978-981-97-5606-3_34

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  • DOI: https://doi.org/10.1007/978-981-97-5606-3_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-5605-6

  • Online ISBN: 978-981-97-5606-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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