An active opinion dynamics model: the gap between the voting result and group opinion

Abstract Originally developed to simulate the evolution of public opinion, opinion dynamics models have also been successfully applied to market pricing and advertising. However, passive interactions initiated by locational or social relationships in these models are insufficient to characterize purposeful behaviours such as canvassing or trading, where people are driven by their specific intrinsic motivations. Here, we propose an active model in which people tend to communicate with someone who is more likely to be an ally and game theoretically decide whether to interact. Model simulations highlight the macroscopic development of opinion evolution, showing the ubiquitous gap between people’s voting result and their collective opinion, and how it narrows with the stabilization of opinion evolution. Our results help explain why group opinion rarely reverses its initial stance and the significance of a level of inclusiveness that is neither too high nor too low. Additionally, we find and attest to the probability distribution of group opinion change, which contributes to predicting how much the collective opinion of a group will change after full discussion.

[1]  Petter Holme,et al.  Collective decision making with a mix of majority and minority seekers. , 2016, Physical review. E.

[2]  R. Horton,et al.  Is actual similarity necessary for attraction? A meta-analysis of actual and perceived similarity , 2008 .

[3]  Guido Caldarelli,et al.  Opinion dynamics on interacting networks: media competition and social influence , 2014, Scientific Reports.

[4]  Adrian Carro,et al.  The Role of Noise and Initial Conditions in the Asymptotic Solution of a Bounded Confidence, Continuous-Opinion Model , 2012, Journal of Statistical Physics.

[5]  Peter Lynn,et al.  How Might Opinion Polls be Improved?: the Case for Probability Sampling , 1996 .

[6]  Jinhu Lü,et al.  Iterative Neighbour-Information Gathering for Ranking Nodes in Complex Networks , 2017, Scientific Reports.

[7]  S. Redner,et al.  Dynamics of confident voting , 2011, 1111.3883.

[8]  Bert Baumgaertner Models of Opinion Dynamics and Mill-Style Arguments for Opinion Diversity , 2018 .

[9]  M. A. Muñoz,et al.  Nonlinear q-voter model. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Jan Lorenz,et al.  A stabilization theorem for dynamics of continuous opinions , 2005, 0708.2981.

[11]  Yucheng Dong,et al.  The fusion process of interval opinions based on the dynamic bounded confidence , 2016, Inf. Fusion.

[12]  Yucheng Dong,et al.  Dynamics of linguistic opinion formation in bounded confidence model , 2016, Inf. Fusion.

[13]  S. Galam Minority opinion spreading in random geometry , 2002, cond-mat/0203553.

[14]  Zhigang Cao,et al.  Fashion and Homophily , 2013, Oper. Res..

[15]  R. Axelrod The Dissemination of Culture , 1997 .

[16]  Enrique Herrera-Viedma,et al.  Consensus Reaching With Time Constraints and Minimum Adjustments in Group With Bounded Confidence Effects , 2020, IEEE Transactions on Fuzzy Systems.

[17]  A. Damasio,et al.  Deciding Advantageously Before Knowing the Advantageous Strategy , 1997, Science.

[18]  Joshua D. Clinton,et al.  An Evaluation of the 2016 Election Polls in the United States , 2018 .

[19]  Jan Lorenz,et al.  Continuous Opinion Dynamics under Bounded Confidence: A Survey , 2007, 0707.1762.

[20]  Ruoyan Sun,et al.  An application of the Continuous Opinions and Discrete Actions (CODA) model to adolescent smoking initiation , 2017, PloS one.

[21]  Guillaume Deffuant,et al.  Mixing beliefs among interacting agents , 2000, Adv. Complex Syst..

[22]  Yucheng Dong,et al.  Uncertain Opinion Evolution with Bounded Confidence Effects in Social Networks , 2019, Journal of Systems Science and Systems Engineering.

[23]  Asuman E. Ozdaglar,et al.  Opinion Fluctuations and Disagreement in Social Networks , 2010, Math. Oper. Res..

[24]  Gang Kou,et al.  A survey on the fusion process in opinion dynamics , 2018, Inf. Fusion.

[25]  P. Clifford,et al.  A model for spatial conflict , 1973 .

[26]  Yi Peng,et al.  Soft consensus cost models for group decision making and economic interpretations , 2019, Eur. J. Oper. Res..

[27]  Robert S. Horton,et al.  A meta-analytic investigation of the processes underlying the similarity-attraction effect , 2013 .

[28]  David Godes,et al.  The Evolution of Influence Through Endogenous Link Formation , 2015, Mark. Sci..

[29]  Andre C. R. Martins,et al.  CONTINUOUS OPINIONS AND DISCRETE ACTIONS IN OPINION DYNAMICS PROBLEMS , 2007, 0711.1199.

[30]  J. T. Cox,et al.  Coalescing Random Walks and Voter Model Consensus Times on the Torus in $\mathbb{Z}^d$ , 1989 .

[31]  Yun Liu,et al.  An opinion diffusion model with clustered early adopters , 2013 .

[32]  S. Redner,et al.  Heterogeneous voter models. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[33]  S. Redner,et al.  Dynamics of vacillating voters , 2007, 0710.0914.

[34]  Yucheng Dong,et al.  Preference evolution model based on Wechat-like interactions , 2019, Knowl. Based Syst..

[35]  Alejandro Ribeiro,et al.  Learning to Coordinate in Social Networks , 2014, Oper. Res..

[36]  Andr'e C. R. Martins,et al.  Opinion Particles: Classical Physics and Opinion Dynamics , 2013, 1307.3304.

[37]  Vittorio Loreto,et al.  Opinion dynamics: models, extensions and external effects , 2016, Participatory Sensing, Opinions and Collective Awareness.

[38]  Donn Byrne,et al.  An Overview (and Underview) of Research and Theory within the Attraction Paradigm , 1997 .

[39]  S. Redner,et al.  Dynamics of non-conservative voters , 2007, 0712.0364.

[40]  Katarzyna Sznajd-Weron,et al.  Opinion evolution in closed community , 2000, cond-mat/0101130.

[41]  Enrique Herrera-Viedma,et al.  Dynamics of Public Opinions in an Online and Offline Social Network , 2017, IEEE Transactions on Big Data.

[42]  Yucheng Dong,et al.  Impact of Social Network Structures on Uncertain Opinion Formation , 2019, IEEE Transactions on Computational Social Systems.

[43]  Mengbin Ye,et al.  Recent Advances in the Modelling and Analysis of Opinion Dynamics on Influence Networks , 2019, Int. J. Autom. Comput..

[44]  M. Degroot Reaching a Consensus , 1974 .

[45]  Rainer Hegselmann,et al.  Opinion dynamics and bounded confidence: models, analysis and simulation , 2002, J. Artif. Soc. Soc. Simul..

[46]  S. Redner,et al.  Ultimate fate of constrained voters , 2004, cond-mat/0405652.

[47]  Gang Kou,et al.  Consensus reaching in social network group decision making: Research paradigms and challenges , 2018, Knowl. Based Syst..

[48]  Francesco Bullo,et al.  Opinion Dynamics and the Evolution of Social Power in Influence Networks , 2015, SIAM Rev..

[49]  Jerry M. Mendel,et al.  Fuzzy Opinion Networks: A Mathematical Framework for the Evolution of Opinions and Their Uncertainties Across Social Networks , 2014, IEEE Transactions on Fuzzy Systems.

[50]  T. Liggett,et al.  Stochastic Interacting Systems: Contact, Voter and Exclusion Processes , 1999 .

[51]  Yucheng Dong,et al.  Opinion dynamics model based on the cognitive dissonance: An agent-based simulation , 2020, Inf. Fusion.

[52]  Gang Kou,et al.  A review on trust propagation and opinion dynamics in social networks and group decision making frameworks , 2019, Inf. Sci..

[53]  Noah E. Friedkin,et al.  Social influence and opinions , 1990 .