Hegselmann–Krause model with environmental noise
HTML articles powered by AMS MathViewer
- by Li Chen, Paul Nikolaev and David J. Prömel;
- Trans. Amer. Math. Soc. 378 (2025), 527-567
- DOI: https://doi.org/10.1090/tran/9289
- Published electronically: October 17, 2024
- HTML | PDF | Request permission
Abstract:
We study a continuous-time version of the Hegselmann–Krause model describing the opinion dynamics of interacting agents subject to random perturbations. Mathematically speaking, the opinion of agents is modelled by an interacting particle system with a non-Lipschitz continuous interaction force, perturbed by idiosyncratic and environmental noises. Sending the number of agents to infinity, we derive a McKean–Vlasov stochastic differential equation as the limiting dynamic, by establishing propagation of chaos for regularized versions of the noisy opinion dynamics. To that end, we prove the existence of a unique strong solution to the McKean–Vlasov stochastic differential equation as well as well-posedness of the associated non-local, non-linear stochastic Fokker–Planck equation.References
- Helmut Abels, Pseudodifferential and singular integral operators, De Gruyter Graduate Lectures, De Gruyter, Berlin, 2012. An introduction with applications. MR 2884718
- Robert A. Adams and John J. F. Fournier, Sobolev spaces, 2nd ed., Pure and Applied Mathematics (Amsterdam), vol. 140, Elsevier/Academic Press, Amsterdam, 2003. MR 2424078
- Cañizares García Ana, On a stochastic particle model of the Keller–Segel equation and its macroscopic limit, Ph.D. thesis, Ludwig Maximilian University of Munich, 2017.
- Arnab Bhattacharyya, Mark Braverman, Bernard Chazelle, and Huy L. Nguyễn, On the convergence of the Hegselmann-Krause system, ITCS’13—Proceedings of the 2013 ACM Conference on Innovations in Theoretical Computer Science, ACM, New York, 2013, pp. 61–65. MR 3385386
- Ismaël Bailleul, Rémi Catellier, and François Delarue, Propagation of chaos for mean field rough differential equations, Ann. Probab. 49 (2021), no. 2, 944–996. MR 4255135, DOI 10.1214/20-aop1465
- Viorel Barbu and Michael Röckner, From nonlinear Fokker-Planck equations to solutions of distribution dependent SDE, Ann. Probab. 48 (2020), no. 4, 1902–1920. MR 4124528, DOI 10.1214/19-AOP1410
- Haim Brezis, Functional analysis, Sobolev spaces and partial differential equations, Universitext, Springer, New York, 2011. MR 2759829, DOI 10.1007/978-0-387-70914-7
- Michele Coghi, Jean-Dominique Deuschel, Peter K. Friz, and Mario Maurelli, Pathwise McKean-Vlasov theory with additive noise, Ann. Appl. Probab. 30 (2020), no. 5, 2355–2392. MR 4149531, DOI 10.1214/20-AAP1560
- Li Chen, Esther S. Daus, Alexandra Holzinger, and Ansgar Jüngel, Rigorous derivation of population cross-diffusion systems from moderately interacting particle systems, J. Nonlinear Sci. 31 (2021), no. 6, Paper No. 94, 38. MR 4319922, DOI 10.1007/s00332-021-09747-9
- Michele Coghi and Franco Flandoli, Propagation of chaos for interacting particles subject to environmental noise, Ann. Appl. Probab. 26 (2016), no. 3, 1407–1442. MR 3513594, DOI 10.1214/15-AAP1120
- Michele Coghi and Benjamin Gess, Stochastic nonlinear Fokker-Planck equations, Nonlinear Anal. 187 (2019), 259–278. MR 3954095, DOI 10.1016/j.na.2019.05.003
- Bernard Chazelle, Quansen Jiu, Qianxiao Li, and Chu Wang, Well-posedness of the limiting equation of a noisy consensus model in opinion dynamics, J. Differential Equations 263 (2017), no. 1, 365–397. MR 3631310, DOI 10.1016/j.jde.2017.02.036
- Ge Chen, Wei Su, Songyuan Ding, and Yiguang Hong, Heterogeneous Hegselmann-Krause dynamics with environment and communication noise, IEEE Trans. Automat. Control 65 (2020), no. 8, 3409–3424. MR 4129689, DOI 10.1109/tac.2019.2956902
- Kai Du and Qingxin Meng, A revisit to $W^n_2$-theory of super-parabolic backward stochastic partial differential equations in $\Bbb R^d$, Stochastic Process. Appl. 120 (2010), no. 10, 1996–2015. MR 2673985, DOI 10.1016/j.spa.2010.06.001
- Giuseppe Da Prato and Jerzy Zabczyk, Stochastic equations in infinite dimensions, 2nd ed., Encyclopedia of Mathematics and its Applications, vol. 152, Cambridge University Press, Cambridge, 2014. MR 3236753, DOI 10.1017/CBO9781107295513
- Kai Du, Jinniao Qiu, and Shanjian Tang, $L^p$ theory for super-parabolic backward stochastic partial differential equations in the whole space, Appl. Math. Optim. 65 (2012), no. 2, 175–219. MR 2891221, DOI 10.1007/s00245-011-9154-9
- Igor Douven and Alexander Riegler, Extending the Hegselmann-Krause model I, Log. J. IGPL 18 (2010), no. 2, 323–335. MR 2647444, DOI 10.1093/jigpal/jzp059
- Kai Du, Shanjian Tang, and Qi Zhang, $W^{m,p}$-solution $(p\geqslant 2)$ of linear degenerate backward stochastic partial differential equations in the whole space, J. Differential Equations 254 (2013), no. 7, 2877–2904. MR 3017034, DOI 10.1016/j.jde.2013.01.013
- Kai Du, $W^{2,p}$-solutions of parabolic SPDEs in general domains, Stochastic Process. Appl. 130 (2020), no. 1, 1–19. MR 4035021, DOI 10.1016/j.spa.2018.12.015
- Stewart N. Ethier and Thomas G. Kurtz, Markov processes, Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics, John Wiley & Sons, Inc., New York, 1986. Characterization and convergence. MR 838085, DOI 10.1002/9780470316658
- Gregory Eady, Jonathan Nagler, Andy Guess, Jan Zilinsky, and Joshua A. Tucker, How many people live in political bubbles on social media? Evidence from linked survey and Twitter data, SAGE Open 9 (2019), no. 1, 2158244019832705.
- Alessio Figalli, Existence and uniqueness of martingale solutions for SDEs with rough or degenerate coefficients, J. Funct. Anal. 254 (2008), no. 1, 109–153. MR 2375067, DOI 10.1016/j.jfa.2007.09.020
- Nicolas Fournier and Benjamin Jourdain, Stochastic particle approximation of the Keller-Segel equation and two-dimensional generalization of Bessel processes, Ann. Appl. Probab. 27 (2017), no. 5, 2807–2861. MR 3719947, DOI 10.1214/16-AAP1267
- Jacob Groshek and Karolina Koc-Michalska, Helping populism win? Social media use, filter bubbles, and support for populist presidential candidates in the 2016 US election campaign, Inform. Commun. Soc. 20 (2017), no. 9, 1389–1407.
- Josselin Garnier, George Papanicolaou, and Tzu-Wei Yang, Consensus convergence with stochastic effects, Vietnam J. Math. 45 (2017), no. 1-2, 51–75. MR 3600416, DOI 10.1007/s10013-016-0190-2
- David Godinho and Cristobal Quiñinao, Propagation of chaos for a subcritical Keller-Segel model, Ann. Inst. Henri Poincaré Probab. Stat. 51 (2015), no. 3, 965–992 (English, with English and French summaries). MR 3365970, DOI 10.1214/14-AIHP606
- Rainer Hegselmann and Ulrich Krause, Opinion dynamics and bounded confidence models, analysis, and simulation, J. Artif. Soc. Social Simul. 5 (2002), no. 3.
- Noorazar Hossein, Recent advances in opinion propagation dynamics: a 2020 survey, Eur. Phys. J. Plus 135 (2020), no. 6, 1–20.
- Hui Huang and Jinniao Qiu, The microscopic derivation and well-posedness of the stochastic Keller-Segel equation, J. Nonlinear Sci. 31 (2021), no. 1, Paper No. 6, 31. MR 4192425, DOI 10.1007/s00332-020-09661-6
- William R. P. Hammersley, David Šiška, and Łukasz Szpruch, Weak existence and uniqueness for McKean-Vlasov SDEs with common noise, Ann. Probab. 49 (2021), no. 2, 527–555. MR 4255126, DOI 10.1214/20-aop1454
- Pierre-Emmanuel Jabin and Zhenfu Wang, Quantitative estimates of propagation of chaos for stochastic systems with $W^{-1,\infty }$ kernels, Invent. Math. 214 (2018), no. 1, 523–591. MR 3858403, DOI 10.1007/s00222-018-0808-y
- M. Kac, Foundations of kinetic theory, Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1954–1955, vol. III, Univ. California Press, Berkeley-Los Angeles, Calif., 1956, pp. 171–197. MR 84985
- Arturo Kohatsu-Higa, Jorge A. León, and David Nualart, Stochastic differential equations with random coefficients, Bernoulli 3 (1997), no. 2, 233–245. MR 1466309, DOI 10.2307/3318589
- N. V. Krylov, An analytic approach to SPDEs, Stochastic partial differential equations: six perspectives, Math. Surveys Monogr., vol. 64, Amer. Math. Soc., Providence, RI, 1999, pp. 185–242. MR 1661766, DOI 10.1090/surv/064/05
- N. V. Krylov, Itô’s formula for the $L_p$-norm of stochastic $W^1_p$-valued processes, Probab. Theory Related Fields 147 (2010), no. 3-4, 583–605. MR 2639716, DOI 10.1007/s00440-009-0217-7
- N. V. Krylov, M. Röckner, and J. Zabczyk, Stochastic PDE’s and Kolmogorov equations in infinite dimensions, Lecture Notes in Mathematics, vol. 1715, Springer-Verlag, Berlin; Centro Internazionale Matematico Estivo (C.I.M.E.), Florence, 1999. Lectures given at the 2nd C.I.M.E. Session held in Cetraro, August 24–September 1, 1998; Edited by G. Da Prato; Fondazione CIME/CIME Foundation Subseries. MR 1730228, DOI 10.1007/BFb0092416
- Ioannis Karatzas and Steven E. Shreve, Brownian motion and stochastic calculus, 2nd ed., Graduate Texts in Mathematics, vol. 113, Springer-Verlag, New York, 1991. MR 1121940, DOI 10.1007/978-1-4612-0949-2
- Thomas G. Kurtz and Jie Xiong, Particle representations for a class of nonlinear SPDEs, Stochastic Process. Appl. 83 (1999), no. 1, 103–126. MR 1705602, DOI 10.1016/S0304-4149(99)00024-1
- Gang Kou, Yiyi Zhao, Yi Peng, and Yong Shi, Multi-level opinion dynamics under bounded confidence, PLOS ONE 7 (2012), no. 9, 1–10.
- Daniel Lacker, On a strong form of propagation of chaos for McKean-Vlasov equations, Electron. Commun. Probab. 23 (2018), Paper No. 45, 11. MR 3841406, DOI 10.1214/18-ECP150
- Giovanni Leoni, A first course in Sobolev spaces, 2nd ed., Graduate Studies in Mathematics, vol. 181, American Mathematical Society, Providence, RI, 2017. MR 3726909, DOI 10.1090/gsm/181
- Lorenz, Consensus strikes back in the Hegselmann–Krause model of continuous opinion dynamics under bounded confidence, J. Artif. Soc. Social Simul. 9 (2006), no. 1.
- Jan Lorenz, Continuous opinion dynamics under bounded confidence: a survey, Int. J. Mod. Phys. C 18 (2007), no. 12, 1819–1838.
- Dustin Lazarovici and Peter Pickl, A mean field limit for the Vlasov-Poisson system, Arch. Ration. Mech. Anal. 225 (2017), no. 3, 1201–1231. MR 3667287, DOI 10.1007/s00205-017-1125-0
- Daniel Lacker, Mykhaylo Shkolnikov, and Jiacheng Zhang, Superposition and mimicking theorems for conditional McKean-Vlasov equations, J. Eur. Math. Soc. (JEMS) 25 (2023), no. 8, 3229–3288. MR 4612111, DOI 10.4171/jems/1266
- Jian-Guo Liu and Rong Yang, Propagation of chaos for large Brownian particle system with Coulomb interaction, Res. Math. Sci. 3 (2016), Paper No. 40, 33. MR 3572548, DOI 10.1186/s40687-016-0086-5
- Olivier Menoukeu-Pamen and Ludovic Tangpi, Strong solutions of some one-dimensional SDEs with random and unbounded drifts, SIAM J. Math. Anal. 51 (2019), no. 5, 4105–4141. MR 4021273, DOI 10.1137/18M1218662
- A. Nedić and B. Touri, Multi-dimensional Hegselmann–Krause dynamics, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012, pp. 68–73.
- Miguel Pineda, Raúl Toral, and Emilio Hernández-García, The noisy Hegselmann-Krause model for opinion dynamics, Eur. Phys. J. B 86 (2013), no. 12, Art. 490, 10. MR 3133787, DOI 10.1140/epjb/e2013-40777-7
- Igor Douven and Alexander Riegler, Extending the Hegselmann-Krause model I, Log. J. IGPL 18 (2010), no. 2, 323–335. MR 2647444, DOI 10.1093/jigpal/jzp059
- B. L. Rozovskiĭ, Stochastic evolution systems, Mathematics and its Applications (Soviet Series), vol. 35, Kluwer Academic Publishers Group, Dordrecht, 1990. Linear theory and applications to nonlinear filtering; Translated from the Russian by A. Yarkho. MR 1135324, DOI 10.1007/978-94-011-3830-7
- Dominic Spohr, Fake news and ideological polarization: Filter bubbles and selective exposure on social media, Bus. Inform. Rev. 34 (2017), no. 3, 150–160.
- Alain-Sol Sznitman, Topics in propagation of chaos, École d’Été de Probabilités de Saint-Flour XIX—1989, Lecture Notes in Math., vol. 1464, Springer, Berlin, 1991, pp. 165–251. MR 1108185, DOI 10.1007/BFb0085169
- Dario Trevisan, Well-posedness of multidimensional diffusion processes with weakly differentiable coefficients, Electron. J. Probab. 21 (2016), Paper No. 22, 41. MR 3485364, DOI 10.1214/16-EJP4453
- Hans Triebel, Interpolation theory, function spaces, differential operators, North-Holland Mathematical Library, vol. 18, North-Holland Publishing Co., Amsterdam-New York, 1978. MR 503903
- Hans Triebel, Theory of function spaces, Monographs in Mathematics, vol. 78, Birkhäuser Verlag, Basel, 1983. MR 781540, DOI 10.1007/978-3-0346-0416-1
- Suttida Wongkaew, Marco Caponigro, and Alfio Borzí, On the control through leadership of the Hegselmann-Krause opinion formation model, Math. Models Methods Appl. Sci. 25 (2015), no. 3, 565–585. MR 3285316, DOI 10.1142/S0218202515400060
- Chu Wang, Qianxiao Li, Weinan E, and Bernard Chazelle, Noisy Hegselmann-Krause systems: phase transition and the $2R$-conjecture, J. Stat. Phys. 166 (2017), no. 5, 1209–1225. MR 3610211, DOI 10.1007/s10955-017-1718-x
- Wei Liu and Michael Röckner, Stochastic partial differential equations: an introduction, Universitext, Springer, Cham, 2015. MR 3410409, DOI 10.1007/978-3-319-22354-4
- Han Xu, Hui Cai, Shuangshuang Wu, Kaili Ai, and Minghua Xu, HKML: A Novel Opinion Dynamics Hegselmann–Krause Model with Media Literacy, 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020, pp. 52–57.
- Kôsaku Yosida, Functional analysis, 6th ed., Grundlehren der Mathematischen Wissenschaften, vol. 123, Springer-Verlag, Berlin-New York, 1980. MR 617913
- Zhou Yang and Shanjian Tang, Dynkin game of stochastic differential equations with random coefficients and associated backward stochastic partial differential variational inequality, SIAM J. Control Optim. 51 (2013), no. 1, 64–95. MR 3032867, DOI 10.1137/110850980
- Xun Yu Zhou, A duality analysis on stochastic partial differential equations, J. Funct. Anal. 103 (1992), no. 2, 275–293. MR 1151549, DOI 10.1016/0022-1236(92)90122-Y
Bibliographic Information
- Li Chen
- Affiliation: Li Chen, University of Mannheim, Germany
- ORCID: 0000-0002-4190-022X
- Email: chen@uni-mannheim.de
- Paul Nikolaev
- Affiliation: Paul Nikolaev, University of Mannheim, Germany
- ORCID: 0009-0005-6963-6730
- Email: pnikolae@mail.uni-mannheim.de
- David J. Prömel
- Affiliation: David J. Prömel, University of Mannheim, Germany
- ORCID: 0000-0001-7028-7500
- Email: proemel@uni-mannheim.de
- Received by editor(s): September 11, 2023
- Received by editor(s) in revised form: June 19, 2024
- Published electronically: October 17, 2024
- Additional Notes: L. Chen acknowledges partial support from the German Research Foundation (DFG), grant CH 955/8-1.
- © Copyright 2024 American Mathematical Society
- Journal: Trans. Amer. Math. Soc. 378 (2025), 527-567
- MSC (2020): Primary 60H15, 60H10, 60K35; Secondary 91D30
- DOI: https://doi.org/10.1090/tran/9289
- MathSciNet review: 4840314