Multi-agent Modeling and Simulation on Group Polarization Behavior in Web 2.0

Under the specific environment of Web 2.0, the formation of Internet users’ opinions online has been impacted a lot. While prior researches do not thoroughly explain the crucial factors to influence group opinion polarization on the Internet. This paper contributes to the literatures, first, by abstracting and integrating key influential factors to group polarization behavior, which are divided by three dimensions: individual, group and topic. Second, establish group polarization model based on multi-agent and after simulation, we find out how these co-determined factors comprehensively affect the performance and which factor influences this behavior most. Additionally, we simulate out the threshold value to generate group polarization behavior in this system, which is 0.2. These results give relative references and implications for further study.

[1]  Erica Briscoe,et al.  A Systems‐Level Understanding of Insurgent Involvement in Improvised Explosive Devices Activities , 2011 .

[2]  Bruce J. MacLennan,et al.  EVOLUTIONARY PSYCHOLOGY, COMPLEX SYSTEMS, AND SOCIAL THEORY , 2007, Soundings: An Interdisciplinary Journal.

[3]  L. Festinger.  A Theory of Social Comparison Processes , 1954 .

[4]  Diane M. Mackie,et al.  Social identification effects in group polarization , 1986 .

[5]  D. Watts,et al.  Influentials, Networks, and Public Opinion Formation , 2007 .

[6]  Frank Leymann,et al.  Identifying influential factors of business process performance using dependency analysis , 2011, Enterp. Inf. Syst..

[7]  S. Bikhchandani,et al.  You have printed the following article : A Theory of Fads , Fashion , Custom , and Cultural Change as Informational Cascades , 2007 .

[8]  Zhenpeng Li,et al.  Social influence,opinion dynamics and structure balance:A simulation study based on Hopfield network model , 2013 .

[9]  M. Macy.  Polarization in Dynamic Networks : A Hopfield Model of Emergent Structure , 2003 .

[10]  L. M. Swol.  Extreme members and group polarization , 2009 .

[11]  John C. Turner,et al.  Social comparison and group interest in ingroup favouritism , 1979 .

[12]  Mohamed Nemiche,et al.  Simulation of the anomalous social behaviours with a learning model , 2011 .

[13]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[14]  Zhu Yunlong,et al.  Knowledge Emergence and Complex Adaptability in Swarm Intelligence , 2005 .

[15]  E. Mitleton-Kelly.  Ten principles of complexity and enabling infrastructures , 2003 .

[16]  Stephen Lansing,et al.  Complex Adaptive Systems , 2003 .

[17]  S. Moscovici,et al.  The group as a polarizer of attitudes. , 1969 .

[18]  M. Kaplan.  Discussion Polarization Effects in a Modified Jury Decision Paradigm: Informational Influences , 1977 .

[19]  LU Guang-yan.  Simulation of the group decision conformity based on cellular automata model , 2009 .

[20]  D. Isenberg.  Group polarization: A critical review and meta-analysis. , 1986 .

[21]  D. Myers,et al.  The group polarization phenomenon. , 1976 .

[22]  LI Yu-xiao.  Research on the Unexpected Emergency and its Social Influence Power Basedon the Coupling Degree Model Between the Intrinsic and Extrinsic Incurring factors , 2012 .

[23]  J. Hottois.  The Spiral of Silence: Public Opinion—Our Social Skin . By Noelle-Neumann Elisabeth. (Chicago: University of Chicago Press, 1984. Pp. xi + 184. $20.00.) , 1985, American Political Science Review.

[24]  INSIGHTS FROM COMPLEXITY THEORY: UNDERSTANDING ORGANIZATIONS BETTER , 2022 .

[25]  M. Hogg,et al.  Knowing what to think by knowing who you are: self-categorization and the nature of norm formation, conformity and group polarization. , 1990, The British journal of social psychology.

[26]  E. Noelle-Neumann.  The Spiral of Silence A Theory of Public Opinion , 1974 .