Research Article
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The Effect of Agents' Psychology and Social Environment on the Opinion Formation: C/PA Relative Agreement Model in SW and SF Societies

Year 2022, Volume 4, Issue 4, 212 - 225, 31.12.2022
https://doi.org/10.51537/chaos.1193078

Abstract

Opinion dynamics in relative agreement models seen as an extension of bounded confidence ones, involve a new agents’ variable usually called opinion uncertainty and have higher level of complexity than that of bounded confidence models. After revising the meaning of the opinion uncertainty variable we conclude that it has to be interpreted as the agent’s opinion toleration, that changes the type of the variable from the social to the psychological one. Since the convergence rates to the stationary states in dynamics of sociological and psychological variables are in general different, we study the effect of agents’ psychology and social environment interaction on the opinion dynamics, using concord and partial antagonism relative agreement model in small-world and scale-free societies. The model considers agents of two psychological types, concord and partial antagonism, that differs it from other relative agreement models. The analysis of opinion dynamics in particular scenarios was used in this work. Simulation results show the importance of this approach, in particular, the effect of small variations in initial conditions on the final state. We found significant mutual influence of opinion and toleration resulting in a variety of statistically stationary states such as quasi consensus, polarization and fragmentation of society into opinion and toleration groups of different configurations. Consensus was found to be rather rare state in a wide range of model parameters, especially in scale-free societies. The model demonstrates different opinion and toleration dynamics in small-world and scale-free societies.

References

  • Abrica-Jacinto, N. L., E. Kurmyshev, and H. A. Juárez, 2017 Effects of the interaction between ideological affinity and psychological reaction of agents on the opinion dynamics in a relative agreement model. Journal of Artificial Societies and Social Simulation 20(3) 3.
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  • Clifford, P. and A. Sudbury, 1973 A model for spatial conflict. Biometrika 60: 581–588.
  • Deffuant, G., 2006 Comparing extremism propagation patterns in continuous opinion models. Journal of Artificial Societies and Social Simulation 9.
  • Deffuant, G., F. Amblard, G. Weisbuch, and T. Faure, 2002 How can extremism prevail? a study based on the relative agreement interaction model. Journal of artificial societies and social simulation 5.
  • Deffuant, G., D. Neau, F. Amblard, and G. Weisbuch, 2001 Mixing beliefs among interacting agents. Advances in Complex Systems p. 11.
  • Dittmer, J. C., 2001 Consensus formation under bounded confidence. Nonlinear Analysis: Theory, Methods & Applications 47: 4615–4621.
  • Dong, Y., M. Zhan, G. Kou, Z. Ding, and H. Liang, 2018 A survey on the fusion process in opinion dynamics. Information Fusion 43: 57–65.
  • Douven, I. and A. Riegler, 2010 Extending the Hegselmann–Krause model i. Logic Journal of IGPL 18: 323–335.
  • French Jr, J. R., 1956 A formal theory of social power. Psychological review 63: 181.
  • Galam, S., 2008 Sociophysics: A review of galam models. International Journal of Modern Physics C 19: 409–440.
  • Hegselmann, R., U. Krause, et al., 2002 Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of artificial societies and social simulation 5.
  • Huang, C., Q. Dai, W. Han, Y. Feng, H. Cheng, et al., 2018 Effects of heterogeneous convergence rate on consensus in opinion dynamics. Physica A: Statistical Mechanics and its Applications 499: 428–435.
  • Kurmyshev, E., H. A. Juárez, and R. A. González-Silva, 2011 Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partial antagonism. Physica A: Statistical Mechanics and its Applications 390: 2945–2955.
  • Lorenz, J., 2008 Fixed points in models of continuous opinion dynamics under bounded confidence. arXiv preprint arXiv:0806.1587.
  • Lorenz, J., 2010 Heterogeneous bounds of confidence: meet, discuss and find consensus! Complexity 15: 43–52.
  • Meadows, M. and D. Cliff, 2012 Reexamining the relative agreement model of opinion dynamics. Journal of Artificial Societies and Social Simulation 15: 4.
  • Pineda, M., R. Toral, and E. Hernández-García, 2013 The noisy Hegselmann-Krause model for opinion dynamics. The European Physical Journal B 86: 1–10.
  • Sznajd-Weron, K. and J. Sznajd, 2000 Opinion evolution in closed community. International Journal of Modern Physics C 11: 1157–1165.
  • Urbig, D. and J. Lorenz, 2007 Communication regimes in opinion dynamics: Changing the number of communicating agents. arXiv preprint arXiv:0708.3334 .
  • Watts, D. J. and S. H. Strogatz, 1998 Collective dynamics of ‘smallworld’networks. nature 393: 440–442.
  • Xia, H., H. Wang, and Z. Xuan, 2011 Opinion dynamics: A multidisciplinary review and perspective on future research. International Journal of Knowledge and Systems Science (IJKSS) 2: 72–91.
  • Yu, Y., V. X. Nguyen, and G. Xiao, 2020 Effects of initial state on opinion formation in complex social networks with noises. arXiv preprint arXiv:2004.00319 .
  • Yu, Y., G. Xiao, G. Li, W. P. Tay, and H. F. Teoh, 2017 Opinion diversity and community formation in adaptive networks. Chaos: An Interdisciplinary Journal of Nonlinear Science 27: 103115.

Year 2022, Volume 4, Issue 4, 212 - 225, 31.12.2022
https://doi.org/10.51537/chaos.1193078

Abstract

References

  • Abrica-Jacinto, N. L., E. Kurmyshev, and H. A. Juárez, 2017 Effects of the interaction between ideological affinity and psychological reaction of agents on the opinion dynamics in a relative agreement model. Journal of Artificial Societies and Social Simulation 20(3) 3.
  • Axelrod, R., 1997 The complexity of cooperation. In The Complexity of Cooperation, Princeton university press.
  • Barabási, A.-L. and R. Albert, 1999 Emergence of scaling in random networks. science 286: 509–512.
  • Clifford, P. and A. Sudbury, 1973 A model for spatial conflict. Biometrika 60: 581–588.
  • Deffuant, G., 2006 Comparing extremism propagation patterns in continuous opinion models. Journal of Artificial Societies and Social Simulation 9.
  • Deffuant, G., F. Amblard, G. Weisbuch, and T. Faure, 2002 How can extremism prevail? a study based on the relative agreement interaction model. Journal of artificial societies and social simulation 5.
  • Deffuant, G., D. Neau, F. Amblard, and G. Weisbuch, 2001 Mixing beliefs among interacting agents. Advances in Complex Systems p. 11.
  • Dittmer, J. C., 2001 Consensus formation under bounded confidence. Nonlinear Analysis: Theory, Methods & Applications 47: 4615–4621.
  • Dong, Y., M. Zhan, G. Kou, Z. Ding, and H. Liang, 2018 A survey on the fusion process in opinion dynamics. Information Fusion 43: 57–65.
  • Douven, I. and A. Riegler, 2010 Extending the Hegselmann–Krause model i. Logic Journal of IGPL 18: 323–335.
  • French Jr, J. R., 1956 A formal theory of social power. Psychological review 63: 181.
  • Galam, S., 2008 Sociophysics: A review of galam models. International Journal of Modern Physics C 19: 409–440.
  • Hegselmann, R., U. Krause, et al., 2002 Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of artificial societies and social simulation 5.
  • Huang, C., Q. Dai, W. Han, Y. Feng, H. Cheng, et al., 2018 Effects of heterogeneous convergence rate on consensus in opinion dynamics. Physica A: Statistical Mechanics and its Applications 499: 428–435.
  • Kurmyshev, E., H. A. Juárez, and R. A. González-Silva, 2011 Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partial antagonism. Physica A: Statistical Mechanics and its Applications 390: 2945–2955.
  • Lorenz, J., 2008 Fixed points in models of continuous opinion dynamics under bounded confidence. arXiv preprint arXiv:0806.1587.
  • Lorenz, J., 2010 Heterogeneous bounds of confidence: meet, discuss and find consensus! Complexity 15: 43–52.
  • Meadows, M. and D. Cliff, 2012 Reexamining the relative agreement model of opinion dynamics. Journal of Artificial Societies and Social Simulation 15: 4.
  • Pineda, M., R. Toral, and E. Hernández-García, 2013 The noisy Hegselmann-Krause model for opinion dynamics. The European Physical Journal B 86: 1–10.
  • Sznajd-Weron, K. and J. Sznajd, 2000 Opinion evolution in closed community. International Journal of Modern Physics C 11: 1157–1165.
  • Urbig, D. and J. Lorenz, 2007 Communication regimes in opinion dynamics: Changing the number of communicating agents. arXiv preprint arXiv:0708.3334 .
  • Watts, D. J. and S. H. Strogatz, 1998 Collective dynamics of ‘smallworld’networks. nature 393: 440–442.
  • Xia, H., H. Wang, and Z. Xuan, 2011 Opinion dynamics: A multidisciplinary review and perspective on future research. International Journal of Knowledge and Systems Science (IJKSS) 2: 72–91.
  • Yu, Y., V. X. Nguyen, and G. Xiao, 2020 Effects of initial state on opinion formation in complex social networks with noises. arXiv preprint arXiv:2004.00319 .
  • Yu, Y., G. Xiao, G. Li, W. P. Tay, and H. F. Teoh, 2017 Opinion diversity and community formation in adaptive networks. Chaos: An Interdisciplinary Journal of Nonlinear Science 27: 103115.

Details

Primary Language English
Subjects Mathematics, Interdisciplinary Applications
Journal Section Research Articles
Authors

Evguenii KURMYSHEV> (Primary Author)
Centro Universitario de los Lagos, Universidad de Guadalajara
0000-0003-2832-5918
Mexico


Norma Leticia ABRİCA JACİNTO This is me
Centro Universitario de los Lagos, Universidad de Guadalajara
0000-0003-0676-1276
Mexico

Publication Date December 31, 2022
Published in Issue Year 2022, Volume 4, Issue 4

Cite

APA Kurmyshev, E. & Abrica Jacinto, N. L. (2022). The Effect of Agents' Psychology and Social Environment on the Opinion Formation: C/PA Relative Agreement Model in SW and SF Societies . Chaos Theory and Applications , Dissemination and Research in the Study of Complex Systems and Their Applications (EDIESCA 2022) , 212-225 . DOI: 10.51537/chaos.1193078

Chaos Theory and Applications in Applied Sciences and Engineering: An interdisciplinary journal of nonlinear science 23830