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Exploring the evolutionary game of rumor control based on prospect theory

  • S.I.: Neural Networks and Machine Learning Empowered Methods and Applications in Healthcare
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Abstract

The increased volume of rumors and attention on related topics during the COVID-19 pandemic have had a significant negative social impact. To combat rumors, it is crucial to study the actors involved in their spread. In this study, we first introduce prospect theory and construct an evolutionary game model between network operators and government regulators. We investigate collusion between network operators and Internet rumormongers as well as the regulatory behavior of government agencies. Second, we use prospect value to replace traditional expected utility to construct a profit prospect matrix and apply the dynamic replicator equation to analyze the equilibrium stability of the model. The stability conditions of the game between the two parties are closely related to the government’s regulatory costs, and the strength of government punishment after collusion is detected. Finally, we propose relevant countermeasures against collusion problems during the network rumor control period.

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Data availability

The data used to support the findings of this study can be obtained from the corresponding author upon request.

References

  1. Ozturk P, Li H, Sakamoto Y (2015) Combating rumor spread on social media: The effectiveness of refutation and warning. In: 2015 48th Hawaii international conference on system sciences. IEEE, pp 2406–2414

  2. Shi H, Shibao S, Lintao Z, Yuxiang L (2018) Research on model of network rumor propagation. In: 2018 5th International conference on information science and control engineering (ICISCE). IEEE, pp 469–472

  3. Islam MS, Kamal AHM, Kabir A, Southern DL, Khan SH, Hasan SM, Seale H et al (2021) COVID-19 vaccine rumors and conspiracy theories: the need for cognitive inoculation against misinformation to improve vaccine adherence. PLoS ONE 16(5):e0251605

    Google Scholar 

  4. Balkin JM (2004) Digital speech and democratic culture: A theory of freedom of expression for the information society. NyuL rev 79:1

    Google Scholar 

  5. Xiang T, Li Q, Li W, Xiao Y (2023) A rumor heat prediction model based on rumor and anti-rumor multiple messages and knowledge representation. Inf Process Manage 60(3):103337

    Google Scholar 

  6. Zhang Y, Xu J (2020) A dynamic competition and predation model for rumor and rumor-refutation. IEEE access 9:9117–9129

    Google Scholar 

  7. Chen J, Wei N, Xin C, Liu M, Yu Z, Liu M (2022) Anti-rumor dissemination model based on heat influence and evolution game. Mathematics 10(21):4064

    Google Scholar 

  8. Guo F, Zhou A, Zhang X, Xu X, Liu X (2023) Fighting rumors to fight COVID-19: investigating rumor belief and sharing on social media during the pandemic. Comput Hum Behav 139:107521

    Google Scholar 

  9. Sun S, Ge X, Wen X, Barrio F, Zhu Y, Liu J (2022) The moderation of human characteristics in the control mechanisms of rumours in social media: the case of food rumours in China. Front Psychol 12:782313

    Google Scholar 

  10. Yin F, Jiang X, Qian X, Xia X, Pan Y, Wu J (2022) Modeling and quantifying the influence of rumor and counter-rumor on information propagation dynamics. Chaos, Solitons Fractals 162:112392

    MathSciNet  Google Scholar 

  11. Wei H, Chen J, Gan X, Liang Z (2022) Eight-element communication model for internet health rumors: a new exploration of lasswell’s “5W communication model.” Healthcare 10(12):2507

    Google Scholar 

  12. Zhang Y, Xu J, Nekovee M, Li Z (2022) The impact of official rumor-refutation information on the dynamics of rumor spread. Phys A Stat Mech Appl 607:128096

    MathSciNet  Google Scholar 

  13. Mou X, Xu W, Zhu Y, Li Q, Xiao Y (2022) A social topic diffusion model based on rumor and anti-rumor and motivation-rumor. IEEE Trans Comput Soc Syst. https://doi.org/10.1109/TCSS.2022.3179435

    Article  Google Scholar 

  14. Sahafizadeh E, Ladani BT (2023) Soft rumor control in mobile instant messengers. Physica A Stat Mech Appl 609:128359

    MathSciNet  Google Scholar 

  15. Chen X, Zhu D, Lin D, Cao D (2021) Rumor knowledge embedding based data augmentation for imbalanced rumor detection. Inf Sci 580:352–370

    MathSciNet  Google Scholar 

  16. Rani N, Das P, Bhardwaj AK (2022) Rumor, misinformation among web: a contemporary review of rumor detection techniques during different web waves. Concurr Comput Pract Exp 34(1):e6479

    Google Scholar 

  17. Slimi H, Bounhas I, Slimani Y (2021) Adapting pre-trained language models to rumor detection on Twitter. JUCS J Univ Comput Sci 27(10):1128–1148

    Google Scholar 

  18. Innes M, Davies B, Lowe T (2019) Counter-governance and ‘post-event prevent’: regulating rumours, fake news and conspiracy theories in the aftermath of terror. Int J Law Crime Justice 72:100370

    Google Scholar 

  19. Chen J, Ma H, Yang S (2023) SEIOR rumor propagation model considering hesitating mechanism and different rumor-refuting ways in complex networks. Mathematics 11(2):283

    MathSciNet  Google Scholar 

  20. Li S, Liu Z, Li Y (2020) Temporal and spatial evolution of online public sentiment on emergencies. Inf Process Manag 57(2):102177

    Google Scholar 

  21. Sartipi F (2020) Organizational structure of construction entities based on the cooperative game theory. J Const Mater 1(2):1

    Google Scholar 

  22. Mailath GJ (1998) Do people play Nash equilibrium? Lessons from evolutionary game theory. J Econ Lit 36(3):1347–1374

    Google Scholar 

  23. Samuelson L (2002) Evolution and game theory. J Econ Perspect 16(2):47–66

    Google Scholar 

  24. Robert X, Gouet P (2014) Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res 42(W1):W320–W324

    Google Scholar 

  25. Srivastava S, Aggarwal A, Bansal P (2022) Efficiency evaluation of assets and optimal portfolio generation by cross efficiency and cumulative prospect theory. Comput Econ. https://doi.org/10.1007/s10614-022-10334-7

    Article  Google Scholar 

  26. Liu S, Ma Y, Chen X (2023) Evolutionary game model based on cumulative prospect theory for information management mechanism in SIoT. Heliyon 9(6):e16590

    Google Scholar 

  27. Luo P, Wang C, Guo F et al (2021) Factors affecting individual online rumor-sharing behavior in the COVID-19 pandemic. Comput Hum Behav 125:106968

    Google Scholar 

  28. Pröllochs N, Bär D, Feuerriegel S (2021) Emotions in online rumor diffusion. EPJ Data Science 10(1):51

    Google Scholar 

  29. Qureshi KA, Malick RAS, Sabih M et al (2021) Complex network and source inspired COVID-19 fake news classification on Twitter. IEEE Access 9:139636–139656

    Google Scholar 

  30. Ahmad T, Faisal MS, Rizwan A et al (2022) Efficient fake news detection mechanism using enhanced deep learning model. Appl Sci 12(3):1743

    Google Scholar 

  31. Shin J, Jian L, Driscoll K et al (2017) Political rumoring on Twitter during the 2012 US presidential election: rumor diffusion and correction. New Media Soc 19(8):1214–1235

    Google Scholar 

  32. Bulumulla C, Singh D, Padgham L et al (2022) Multi-level simulation of the physical, cognitive, and social. Comput Environ Urban Syst 93:101756

    Google Scholar 

  33. Dong Y, Zhao L (2022) An improved two-layer model for rumor propagation considering time delay and event-triggered impulsive control strategy. Chaos Solitons Fractals 164:112711

    MathSciNet  Google Scholar 

  34. Zhu L, Liu W, Zhang Z (2020) Delay differential equations modeling of rumor propagation in homogeneous and heterogeneous networks with a forced silence function. Appl Math Comput 370:124925

    MathSciNet  Google Scholar 

  35. Liu B, Sun X, Meng Q et al (2022) Nowhere to hide online rumor detection based on retweeting graph neural networks. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2022.3161697

    Article  Google Scholar 

  36. Yang Y, Zeng Y, Dai J et al (2021) The evolutionary game analysis of public opinion supervision of engineering quality in the network citizen journalism environment. Mob Inf Syst 2021:1–12

    Google Scholar 

  37. Chen H, Zhao X (2022) Modeling and simulation research of interactive public opinion evolution under multi-agent interventions. Processes 10(7):1379

    Google Scholar 

  38. Xiao Y, Chen D, Wei S et al (2019) Rumor propagation dynamic model based on evolutionary game and anti-rumor. Nonlinear Dyn 95:523–539

    Google Scholar 

  39. Li D, Ma J, Tian Z et al (2015) An evolutionary game for rumor diffusion in complex networks. Physica A Stat Mech Appl 433:51–58

    Google Scholar 

  40. Levy JS (2003) Applications of prospect theory to political science. Synthese 135:215–241

    MathSciNet  Google Scholar 

  41. DiFonzo N and Bordia P (2007) Rumors influence: toward a dynamic social impact theory of rumor (Doctoral dissertation, Psychology Press).

  42. Ye P, Liu L, Tan J (2022) Influencing factors on college students’ willingness to spread internet public opinion: analysis based on COVID-19 data in China. Front Public Health 10:772833

    Google Scholar 

  43. Reichenbach F, Walther M (2023) Financial recommendations on reddit, stock returns and cumulative prospect theory. Digit Financ. https://doi.org/10.1007/s42521-023-00084-y

    Article  Google Scholar 

  44. Whittington R, Yakis-Douglas B (2020) The grand challenge of corporate control: opening strategy to the normative pressures of networked professionals. Organ Theory 1(4):2631787720969697

    Google Scholar 

  45. Wang Y, Wang C, Deng X, Wu Z (2023) Evolutionary game analysis of the utilization of construction waste resources based on prospect theory. Sustainability 15(3):2577

    Google Scholar 

  46. Bhattacharyya S, Vutha A, Bauch CT (2019) The impact of rare but severe vaccine adverse events on behaviour-disease dynamics: a network model. Sci Rep 9(1):7164

    Google Scholar 

  47. Zhao H, Liu X, Wang Y (2021) Tripartite evolutionary game analysis for rumor spreading on Weibo based on MA-PT. Ieee Access 9:90043–90060

    Google Scholar 

  48. Ricciardi V, Simon HK (2000) What is behavioral finance? Bus Educ Technol J 2(2):1–9

    Google Scholar 

  49. Flannery MJ (1998) Using market information in prudential bank supervision: a review of the US empirical evidence. J Money Credit Bank 30(3):273–305

    Google Scholar 

  50. Kahneman D, Tversky A (1979) Prospect theory: analysis of decision under ris. Econometrica 47(2):263–291

    MathSciNet  Google Scholar 

  51. Gu J, Zheng Y, Tian X, Xu Z (2021) A decision-making framework based on prospect theory with probabilistic linguistic term sets. J Operat Res Soc 72(4):879–888

    Google Scholar 

  52. An M, Liu M, An H, Ramsey TS (2023) Systematic evaluation of emergency management capacity for rural public health emergencies. Int J Disaster Risk Reduct 85:103493

    Google Scholar 

  53. Harwit E, Clark D (2001) Shaping the internet in China. Evolution of political control over network infrastructure and content. Asian Surv 41(3):377–408

    Google Scholar 

  54. Friedman D (1998) Oneconomic applications of evolutionary game theory. J Evolut Econom 8:15–43

    Google Scholar 

  55. Taylor PD, Jonker LB (1979) Evolutionarily stable strategies and game dynamics. J Theoret Biol 81(3):609–612

    MathSciNet  Google Scholar 

  56. Friedman D (1991) Evolutionary games in economics. Econometrica 59(3):637–666

    MathSciNet  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 72201173), Education and Scientific Research Project of Shanghai (No. C2023292), the National Key R&D Program of China (Grant 2021YFF0900400), the Open Project Program of Shanghai Innovation Reverse Logistics and Supply Center of Chain.

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Authors and Affiliations

  1. Business School, University of Shanghai for Science and Technology, Shanghai, 200093, People’s Republic of China

    Jinghua Zhao, Ting Lan & Haiying Rong

  2. Department of Intensive Care Unit, The Affiliated TCM Hospital of Guangzhou Medical University, 16 Zhuji Rd, Guangzhou, 510000, Guangdong, People’s Republic of China

    Shanshan Liu

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  1. Jinghua Zhao
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  4. Shanshan Liu
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Correspondence to Shanshan Liu.

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Zhao, J., Lan, T., Rong, H. et al. Exploring the evolutionary game of rumor control based on prospect theory. Neural Comput & Applic 36, 9675–9685 (2024). https://doi.org/10.1007/s00521-023-09027-5

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