IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v490y2018icp260-268.html
   My bibliography  Save this article

Naming game with biased assimilation over adaptive networks

Author

Listed:
  • Fu, Guiyuan
  • Zhang, Weidong

Abstract

The dynamics of two-word naming game incorporating the influence of biased assimilation over adaptive network is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he may refuse to accept the conveyed word from the speaker with a predefined probability, if the conveyed word is different from his current memory. Secondly, the adaptive network is formulated by rewiring the links. Theoretical analysis is developed to show that the population in NGBA will eventually reach global consensus on either A or B. Numerical simulation results show that the larger strength of biased assimilation on both words, the slower convergence speed, while larger strength of biased assimilation on only one word can slightly accelerate the convergence; larger population size can make the rate of convergence slower to a large extent when it increases from a relatively small size, while such effect becomes minor when the population size is large; the behavior of adaptively reconnecting the existing links can greatly accelerate the rate of convergence especially on the sparse connected network.

Suggested Citation

  • Fu, Guiyuan & Zhang, Weidong, 2018. "Naming game with biased assimilation over adaptive networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 260-268.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:260-268
    DOI: 10.1016/j.physa.2017.08.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117307409
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2017.08.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Run-Ran & Jia, Chun-Xiao & Yang, Han-Xin & Wang, Bing-Hong, 2009. "Naming game on small-world networks with geographical effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3615-3620.
    2. Fu, Guiyuan & Cai, Yunze & Zhang, Weidong, 2017. "Analysis of naming game over networks in the presence of memory loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 350-361.
    3. Jan Lorenz, 2007. "Continuous Opinion Dynamics Under Bounded Confidence: A Survey," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(12), pages 1819-1838.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lou, Yang & Chen, Guanrong & Hu, Jianwei, 2018. "Communicating with sentences: A multi-word naming game model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 857-868.
    2. Bertrand Jayles & Clément Sire & Ralf H J M Kurvers, 2021. "Crowd control: Reducing individual estimation bias by sharing biased social information," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-28, November.
    3. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    4. Dimitris Tsintsaris & Milan Tsompanoglou & Evangelos Ioannidis, 2024. "Dynamics of Social Influence and Knowledge in Networks: Sociophysics Models and Applications in Social Trading, Behavioral Finance and Business," Mathematics, MDPI, vol. 12(8), pages 1-27, April.
    5. Riazi, Diana & Livan, Giacomo, 2024. "Public and private beliefs under disinformation in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    6. Fu, Guiyuan & Zhang, Weidong, 2016. "Opinion formation and bi-polarization with biased assimilation and homophily," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 700-712.
    7. Guillaume Deffuant & Ilaria Bertazzi & Sylvie Huet, 2018. "The Dark Side Of Gossips: Hints From A Simple Opinion Dynamics Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-20, September.
    8. G Jordan Maclay & Moody Ahmad, 2021. "An agent based force vector model of social influence that predicts strong polarization in a connected world," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-42, November.
    9. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    10. Song, Xiao & Shi, Wen & Tan, Gary & Ma, Yaofei, 2015. "Multi-level tolerance opinion dynamics in military command and control networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 322-332.
    11. Song, Xiao & Zhang, Shaoyun & Qian, Lidong, 2013. "Opinion dynamics in networked command and control organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5206-5217.
    12. Nizamani, Sarwat & Memon, Nasrullah & Galam, Serge, 2014. "From public outrage to the burst of public violence: An epidemic-like model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 620-630.
    13. Antonio Parravano & Ascensión Andina-Díaz & Miguel A Meléndez-Jiménez, 2016. "Bounded Confidence under Preferential Flip: A Coupled Dynamics of Structural Balance and Opinions," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-23, October.
    14. Sylvie Huet & Jean-Denis Mathias, 2018. "Few Self-Involved Agents Among Bounded Confidence Agents Can Change Norms," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-27, September.
    15. Shin, J.K., 2009. "Information accumulation system by inheritance and diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3593-3599.
    16. Li, Mingwu & Dankowicz, Harry, 2019. "Impact of temporal network structures on the speed of consensus formation in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1355-1370.
    17. Kurmyshev, Evguenii & Juárez, Héctor A. & González-Silva, Ricardo A., 2011. "Dynamics of bounded confidence opinion in heterogeneous social networks: Concord against partial antagonism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2945-2955.
    18. Fu, Guiyuan & Cai, Yunze & Zhang, Weidong, 2017. "Analysis of naming game over networks in the presence of memory loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 350-361.
    19. Shane T. Mueller & Yin-Yin Sarah Tan, 2018. "Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization," Journal of Computational Social Science, Springer, vol. 1(1), pages 15-48, January.
    20. Castro, Luis E. & Shaikh, Nazrul I., 2018. "A particle-learning-based approach to estimate the influence matrix of online social networks," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 1-18.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:260-268. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.