Modeling of the Public Opinion Polarization Process with the Considerations of Individual Heterogeneity and Dynamic Conformity

Nowadays, hot issues are likely become bipolar or multipolar after heated discussion on the Internet. This article is focused on the study of the polarization phenomenon and establishes a public opinion polarization model with the considerations of individual heterogeneity and dynamic conformity. At first, this article introduces the dynamic changing function of an individual’s conformity tendency to other’s attitudes in the interaction process. It further defines the influential weight between different interactive individuals, and expands the interactive individual from complete homogeneity to initial attitude heterogeneity, and finally, conformity heterogeneity. Then, through simulation experiments, we find that the degree of changing in individual attitude is limited. That is, it is difficult for the individuals who have one directional attitude at the initial time to change into another opposite attitude through interaction. In addition, individuals with low conformity within a certain threshold are more likely to form polarization. Finally, the rationality and effectiveness of the proposed model are verified by the typical case “Mimeng Event”.

[1]  Dolores Albarracín,et al.  Debunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation , 2017, Psychological science.

[2]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[3]  M. Olson,et al.  The Economics of Autocracy and Majority Rule: The Invisible Hand and the Use of Force , 1996 .

[4]  Francisco José León Medina,et al.  Endogenous Changes in Public Opinion Dynamics , 2019, J. Artif. Soc. Soc. Simul..

[5]  Jon A. Krosnick,et al.  Perception of public opinion on global warming and the role of opinion deviance , 2019, Journal of Environmental Psychology.

[6]  V. Manuel.,et al.  Looking for a physical basis of rainfall multifractality , 2020 .

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

[8]  Mala Pande,et al.  Differences in nativity, age and gender may impact health behavior and perspectives among Asian Indians , 2019, Ethnicity & health.

[9]  Gongfa Li,et al.  Enhancing network cluster synchronization capability based on artificial immune algorithm , 2019, Human-centric Computing and Information Sciences.

[10]  Wander Jager,et al.  Uniformity, Bipolarization and Pluriformity Captured as Generic Stylized Behavior with an Agent-Based Simulation Model of Attitude Change , 2005, Comput. Math. Organ. Theory.

[11]  E. Ising Beitrag zur Theorie des Ferromagnetismus , 1925 .

[12]  L. Bode,et al.  See Something, Say Something: Correction of Global Health Misinformation on Social Media , 2018, Health communication.

[13]  Tuuli-Marja Kleiner,et al.  Public opinion polarisation and protest behaviour , 2018 .

[14]  Stanley Milgram,et al.  An Experimental Study of the Small World Problem , 1969 .

[15]  Ananthram Swami,et al.  Consensus, Polarization and Clustering of Opinions in Social Networks , 2013, IEEE Journal on Selected Areas in Communications.

[16]  K. Goh,et al.  Universal behavior of load distribution in scale-free networks. , 2001, Physical review letters.

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

[18]  Jonas Colliander,et al.  "This is fake news": Investigating the role of conformity to other users' views when commenting on and spreading disinformation in social media , 2019, Comput. Hum. Behav..

[19]  Karl E. Kürten,et al.  PHYSICS OF THE MIND: OPINION DYNAMICS AND DECISION MAKING PROCESSES BASED ON A BINARY NETWORK MODEL , 2008 .

[20]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[21]  Ann E. Schlosser,et al.  Who's Driving this Conversation? Systematic Biases in the Content of Online Consumer Discussions , 2017 .

[22]  Zhijun Li,et al.  Opinion dynamics of modified Hegselmann–Krause model in a group-based population with heterogeneous bounded confidence , 2015 .

[23]  Guillaume Deffuant,et al.  Models of Social Influence: Towards the Next Frontiers , 2017, J. Artif. Soc. Soc. Simul..

[24]  Cass R. Sunstein,et al.  Neither Hayek nor Habermas , 2007 .

[25]  Zhangxi Lin,et al.  Investigating the opinions distribution in the controversy on social media , 2019, Inf. Sci..

[26]  R. Holley,et al.  Ergodic Theorems for Weakly Interacting Infinite Systems and the Voter Model , 1975 .

[27]  Stephan Lewandowsky,et al.  Influence and seepage: An evidence-resistant minority can affect public opinion and scientific belief formation , 2019, Cognition.

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

[29]  Dino Pedreschi,et al.  Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model , 2018, PloS one.

[30]  David Lee,et al.  Biased assimilation, homophily, and the dynamics of polarization , 2012, Proceedings of the National Academy of Sciences.

[31]  Kar-Hai Chu,et al.  Tobacco Use Behaviors, Attitudes, and Demographic Characteristics of Tobacco Opinion Leaders and Their Followers: Twitter Analysis , 2019, Journal of medical Internet research.

[32]  Tamer Basar,et al.  Game-Theoretic Analysis of the Hegselmann-Krause Model for Opinion Dynamics in Finite Dimensions , 2014, IEEE Transactions on Automatic Control.

[33]  Jin Li,et al.  Agent-Based Modelling Approach for Multidimensional Opinion Polarization in Collective Behaviour , 2017, J. Artif. Soc. Soc. Simul..

[34]  Yves Zenou,et al.  Strong Versus Weak Ties in Migration , 2014, SSRN Electronic Journal.

[35]  A. Daly,et al.  The Lead Igniter: A Longitudinal Examination of Influence and Energy Through Networks, Efficacy, and Climate , 2018, Educational Administration Quarterly.

[36]  Kaiping Zhang,et al.  Encountering Dissimilar Views in Deliberation: Political Knowledge, Attitude Strength, and Opinion Change , 2018, Political Psychology.

[37]  Guillaume Deffuant,et al.  How can extremism prevail? A study based on the relative agreement interaction model , 2002, J. Artif. Soc. Soc. Simul..

[38]  Roberto Tempo,et al.  Novel Multidimensional Models of Opinion Dynamics in Social Networks , 2015, IEEE Transactions on Automatic Control.

[39]  David J. Atkin,et al.  To comment or not to comment: Examining the influences of anonymity and social support on one’s willingness to express in online news discussions , 2018, New Media Soc..

[40]  M. Gentzkow,et al.  Social Media and Fake News in the 2016 Election , 2017 .

[41]  Stanley Milgram,et al.  An Experimental Study of the Small World Problem , 1969 .

[42]  Francisco J. León-Medina Endogenous Changes in Public Opinion Dynamics , 2019 .