A Coevolutionary Opinion Model Based on Bounded Confidence, Reference Range, and Interactive Influence in Social Network

  • Chao YangEmail author
Part of the Agent-Based Social Systems book series (ABSS, volume 12)


The rapid development of Web 2.0 technology has made social network platform become an important place for opinion generation, exchange, and dissemination. Thus, the study of opinion evolution via social network has important theoretical and practical significance. In this paper, we propose an coevolutionary opinion model of social network based on bounded confidence, reference range, and interactive influence. First, a dual opinion structure is defined, which considers both inward attitude and outward appearance to reflect the constitution and expression of individual opinion. Second, the interactive mechanisms between individuals are captured through two types of social relationships as authority and familiarity. Then, each individual is assigned a reference set and a trust set based on the individual influence model and bounded confidence model. In order to connect the micro-opinion update behavior and macro-network evolution phenomenon in such situation, an agent-based coevolutionary opinion model is proposed based on multidimensional time-varying interactive influence of users. Three groups of simulation experiments have been conducted to compare the system dynamics under different values of confidence threshold, reference set size, and social relationship influence. The obtained results are found in good agreement with what has happened in the bounded confidence model, but more accord with the people behavior characteristics of opinion interaction under the network environment, which would help us to better understand the internal mechanism of opinion dynamics and social network evolutions.


  1. Axelrod R (1997) The dissemination of culture: a model with local convergence and global polarization. J Confl Resolut 41(2):203–226CrossRefGoogle Scholar
  2. Deffuant G, Neau D, Amblard F (2000) Mixing beliefs among interacting agents. Adv Complex Syst 3(4):87–98CrossRefGoogle Scholar
  3. De Sanctis L, Galla T (2009) Effects of noise and confidence thresholds in nominal and metric Axelrod dynamics of social influence. Phys Rev E 79(4):46–54CrossRefGoogle Scholar
  4. Diao SM, Liu Y, Zeng QA, Luo GX, Xiong F (2014) A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks. Phys A Stat Mech Appl 415:220–228CrossRefGoogle Scholar
  5. Gracia-Lzaro C, Quijandra F, Hernndez L, Flora LM, Moreno Y (2011) Coevolutionary network approach to cultural dynamics controlled by intolerance. Phys Rev E 84(06):76–84Google Scholar
  6. Hegselmann R, Krause U (2002) Opinion dynamics and bounded confidence models, analysis, and simulations. J Artif Soc Soc Simul 5(3):2Google Scholar
  7. Kurmyshev E, Juarez HA, Gonzalez-Silva RA (2011) Dynamics of bounded confidence opinion in heterogeneous social networks: concord against partial antagonism. Phys A Stat Mech Appl 390(16):2945–2955CrossRefGoogle Scholar
  8. Martins AC (2008a) Continuous opinions and discrete actions in opinion dynamics problems. Int J Modem Phys C 19(04):617–624CrossRefGoogle Scholar
  9. Martins AC (2008b) Mobility and social network effects on extremist opinions. Phys Rev E 78(03):36104CrossRefGoogle Scholar
  10. Martins AC, Kuba CD (2010) The importance of disagreeing: contrarians and extremism in the coda model. Adv Complex Syst 13(05):621–634CrossRefGoogle Scholar
  11. Su J, Liu B, Li Q, Ma H (2014) Coevolution of opinions and directed adaptive networks in a social group. J Artif Soc Soc Simul 17(02):611–617CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Computer Science and Electronic EngineeringHunan UniversityChangshaChina

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