DOI
10.34229/KCA2522-9664.25.5.1
UDC 681.51: 519.71
О. Palagin
Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine,
palagin_a@ukr.net
D. Symonov
Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine,
denys.symonov@gmail.com
FORMALIZED MODEL OF ATTITUDE FORMATION
AS A TOOL FOR ANALYZING BEHAVIORAL PATTERNS
Abstract. The article presents a model of attitude formation that enables the analysis of individual behavioral patterns in complex social systems. The proposed model is based on dynamic systems and considers the balance between rationality and the utility of decision-making. The concept of a harmony index is introduced, describing the interaction between internal and external factors, along with a rationality function, which determines the degree of alignment between decisions and an individual’s cognitive predispositions. Special attention is given to the influence of the informational environment on the decision-making process, modeled through an entropy-based approach to analyzing informational noise and manipulations. A mathematical description of attitude adaptation is provided, and a logistic model of attitude change under the influence of external factors is proposed. The study has practical significance for predicting social group behavior, assessing the stability of social systems, and investigating the mechanisms of informational influence.
Keywords: dynamic systems, behavior dynamics, harmony index, rationality function, utility function.
full text
REFERENCES
- 1. Pinker S. Rationality: What It Is, Why It Seems Scarce, Why It Matters. New York: Viking, 2021. 412 p.
- 2. Habermas J. The theory of communicative action. Vol. 1. Reason and the Rationalization of Society. Boston: Beacon Press, 1984. 465 p.
- 3. Ross W. Accidental Thinking: A model of serendipity’s cognitive processes. Review of General Psychology. 2024. Vol. 28, N 3. P. 253–267. https://doi.org/10.1177/10892680241254759.
- 4. Steinbruner J.D. The Analytic Paradigm. In The Cybernetic Theory of Decision: New Dimensions of Political Analysis. Princeton: Princeton University Press, 1974. 368 p. https://doi.org/10.2307/j.ctv1nxctxf.
- 5. Simonov D.I., Zaika, B.Yu. Modeling of management of complex information multicomponent systems. Scientific Bulletin of Uzhgorod University. Series "Mathematics and Informatics". 2024. Vol. 44, No. 1. P. 168–174. https://doi.org/10.24144/2616-7700.2024.44(1).168-174.
- 6. Palagin O.V. Cybernetics and controlled evolution. Cybernetics and Computer Technologies. 2023. No. 1. P. 5–12. https://doi.org/10.34229/2707-451X.23.1.1.
- 7. Wang F., Liu C. Cognitive processes in rule violation. Advances in Cognitive Psychology. 2024. Vol. 20, N 1. P. 35–43. https://doi.org/10.5709/acp-0414-5.
- 8. Palagin O.V., Simonov D.I. Cybernetic model of a rational world order in the paradigm of controlled evolution. International scientific and technical journal "Problems of control and computer science". 2023. Vol. 67, No. 6. P. 54–66. https://»doi.org/10.34229/1028-0979-2022-6-5.
- 9. Cavana R.Y., Dangerfield B.C., Pavlov O.V., Radzicki M.J., Wheat I.D. Feedback Economics. Economic Modeling with System Dynamics. Switzerland: Springer Cham, 2021. 593 p. https://doi.org/10.1007/978-3-030-67190-7.
- 10. Bing Liu. Sentiment Analysis. Mining Opinions, Sentiments, and Emotions. 2nd Edition. Cambridge: Cambridge University Press, 2020. 448 p.
- 11. Masao Ogaki, Saori C. Tanaka. Behavioral Economics. Toward a New Economics by Integration with Traditional Economics. Singapore: Springer Nature Singapore Pte Ltd, 2017. 211 p. https://doi.org/10.1007/978-981-10-6439-5.
- 12. Roman D., Ari N., Mell J. The Harmony Index: Evaluating, Predicting, and Visualizing Effectiveness in Multi-Agent Team Dynamics. Proc. of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 2024. Vol. 20, N 1. P. 97–106. https://doi.org/10.1609/aiide.v20i1.31870.
- 13. Thaler R.H. Misbehaving: The Making of Behavioral Economics. W. W. Norton & Company, 2015. 432 p.
- 14. Kahneman D. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2013. 512 p.
- 15. Bass F.M. A new product growth for model consumer durables. Management Science. 1969. Vol. 15, N 5. Р. 215–227.
- 16. Simonov D.I. Entropy maximization method for predicting the behavior of complex systems under noise conditions. Journal of Computational and Applied Mathematics. 2025. No. 2. P. 52–61. https://doi.org/10.17721/2706-9699.2024.2.03.
- 17. Krämer W., Kahneman D. (2011): Thinking, fast and slow. Stat Papers. 2014. Vol. 55, P. 915. https://doi.org/10.1007/s00362-013-0533-y.
- 18. Simon H.A. Designing organizations for an information-rich world. In M. Greenberger (Ed.), Computers, Communications, and the Public Interest. Johns Hopkins Press. 1971. Р. 37–72.
- 19. Shannon C.E. A mathematical theory of communication. The Bell System Technical Journal. 1948. Vol. 27, N 3. P. 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
- 20. Kazuhisa Takemura. Escaping from Bad Decisions. A Behavioral Decision-Theoretic Perspective. Academic Press, 2021. 542 p.
