Mathematical model assessing the information impact on the electorate in social media during election campaigns
Matematičeskoe modelirovanie, Tome 33 (2021) no. 12, pp. 67-81.

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In the article, a mathematical model for assessing the information impact on the electorate in social media during election campaigns is developed. It is based on well-known mathematical models of information warfare in a structured society and differs from them by taking into account the stochastic nature of the intensity of information dissemination from external sources. The resulting model is reduced to a system of stochastic differential equations, understood in the sense of Ito. The estimate of the number of adepts and pre-adepts who give preference to the candidate in the election campaign is given by the sample average, which is calculated by the probability density function determined from the solution of the Fokker–Planck–Kolmogorov equation. The solution of the Fokker–Planck–Kolmogorov equation is performed according to the proposed numerical scheme based on the projection formulation of the Galerkin method. The results of the simulation in relation to the test problem are presented.
Keywords: mathematical model, information impact assessment, election campaign, social media, Galerkin method.
Mots-clés : Fokker–Planck–Kolmogorov equation
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I. S. Poljanskij; K. O. Loginov; N. I. Ilyin; A. S. Velikikh. Mathematical model assessing the information impact on the electorate in social media during election campaigns. Matematičeskoe modelirovanie, Tome 33 (2021) no. 12, pp. 67-81. http://geodesic.mathdoc.fr/item/MM_2021_33_12_a4/

[1] D. P. Gavra, “Obshchestvennoe mnenie i vlast'. Rezhimy i mekhanizmy vzaimodejstviya”, ZHurnal sociologii i social'noj antropologii, 1:4 (1998), 53–77

[2] G. B. Pronchev, V. I. Murav'ev, “Social'nye seti kak faktor perekhoda Rossii k innovacionnomu razvitiyu”, Sociologiya, 2011, no. 3, 36–56

[3] S. G. Davydov, “«Open opinion» project as a social experiment: interactions with mass media and social media”, Sociological Journal, 2012, no. 1, 118–138

[4] A. P. Petrov, A. I. Maslov, N. A. Tsaplin, “Modeling Position Selection by Individuals during Information Warfare in Society”, Mathematical Models and Computer Simulations, 8:4 (2016), 401–408 | DOI | Zbl

[5] A. P. Mikhailov, A. P. Petrov, G. B. Pronchev, O. G. Proncheva, “Modeling a Decrease in Public Attention to a Past One-Time Political Event”, Doklady Mathematics, 97:3 (2018), 247–249 | DOI | DOI

[6] A. P. Petrov, O. G. Proncheva, “Modeling Position Selection by Individuals during Informational Warfare with a Two-Component Agenda”, MM CS, 12:2 (2020), 154–163 | Zbl

[7] A. A. Samarskii, A. P. Mikhailov, Principles of mathematical modelling: Ideas, methods, examples, CRC Press

[8] A. P. Mikhailov, A. P. Petrov, N. A. Marevtseva, I. V. Tretiakova, “Development of a model of information dissemination in society”, Mathematical Models and Computer Simulations, 6:5 (2014), 535–541 | DOI | Zbl

[9] K. V. Gardiner, Stohasticheskie metody v estestvennyh naukah, Mir, M., 1986, 528 pp.

[10] D. F. Kuznetsov, CHislennoe modelirovanie stohasticheskih differencial'nyh uravnenij i stohasticheskih integralov, Nauka, Sankt-Peterburg, 1999, 459 pp.

[11] D. F. Kuznetsov, “Some Problems in the Theory of the Numerical Solution of Ito Stochastic Differential Equations”, Electronic Journal “Differential Equations and Control Processes”, 1998, no. 1, 66–367 | DOI

[12] I. I. Gihman, A. V. Skorohod, Vvedenie v teoriyu sluchajnyh processov, Nauka, M., 1977, 660 pp.

[13] H. Federer, Geometric measure theory, Springer, New York, 1969 | Zbl

[14] V. I. Tihonov, M. A. Mironov, Markovskie processy, Sov. radio, M., 1977, 488 pp.

[15] I. S. Poljanskij, N. S. Arkhipov, S. Yu. Misyurin, “On solving the optimal control problem”, Automation and Remote Control, 80:1 (2019), 66–80 | DOI

[16] I. S. Poljanskij, “Baricentricheskij metod v zadache optimal'nogo upravleniya formoj otrazhayushchej poverhnosti zerkal'noj antenny”, Matem. Model., 29:11 (2017), 140–150

[17] P. A. Aleksandrov, B. A. Pasynkov, Vvedenie v teoriyu razmernosti. Vvedenie v teoriyu topologicheskih prostranstv i obshchuyu teoriyu razmernosti, Nauka, M., 1973, 576 pp.

[18] I. S. Poljanskij, D. E. Stepanov, D. K. Ketukh, V. A. Shevchenko, “Elektrodinamicheskij analiz zerkal'nyh antenn v priblizhenii baricentricheskogo metoda”, Fizika volnovyh processov i radiotekhnicheskie sistemy, 23:4 (2020), 36–47 | DOI

[19] J. R. Dormand, P. J. Prince, “A family of embedded Runge-Kutta formulae”, J. Comp. Appl. Math., 6:1 (1980), 19–26 | DOI | Zbl

[20] A. Genz, R. Cools, “An adaptive numerical cubature algorithm for simplices”, Mathematics, Comp. Sci. ACM Trans. Math. Softw., 29 (2003), 297–308 | DOI | Zbl

[21] Z. Chen, “Bayesian filtering: from Kalman filters to particle filters, and beyond. Statistics”, Journal of Theoretical and Applied Statistics, 182:11 (2003), 1–69