IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v523y2019icp1355-1370.html
   My bibliography  Save this article

Impact of temporal network structures on the speed of consensus formation in opinion dynamics

Author

Listed:
  • Li, Mingwu
  • Dankowicz, Harry

Abstract

Opinion dynamics on networks has wide applications to empirical and engineered systems and profound prospects in the general study of complex systems. Many efforts have been devoted to understanding how opinion dynamics is affected by network topology. However, social interactions are best characterized as temporal networks in which ordering of interactions cannot be ignored. Temporal activity patterns including heterogeneous contact strength and interevent times, turnover edge/node dynamics, and daily patterns could have significant effects that would not be captured by static aggregate network representations. In this paper, we study the effects of such temporal patterns on the speed of consensus formation in various models of continuous opinion dynamics using four empirical data sets, including three human face-to-face networks from different real-world settings and a social insect interaction network. We find that static, aggregated networks consistently overestimate the speed of simulated consensus formation while weight heterogeneity associated with frequency of interactions has an inhibitory effect on consensus formation relative to the behavior on unweighted networks. Moreover, the speed of consensus formation is found to be highly sensitive to nodal lifetimes, suggesting that randomization protocols that dramatically alter the distribution of lifetimes cannot be relied upon as reference models. On the other hand, temporal patterns including burstiness of interevent times and the lifetime of edges are found to have insignificant effects on consensus formation. The sensitivity to nodal lifetimes is further demonstrated via synthetic networks generated by an activity-driven model with tunable nodal lifetimes.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:523:y:2019:i:c:p:1355-1370
    DOI: 10.1016/j.physa.2019.04.206
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119305746
    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.2019.04.206?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. 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.
    2. Gandica, Yérali & del Castillo-Mussot, Marcelo & Vázquez, Gerardo J. & Rojas, Sergio, 2010. "Continuous opinion model in small-world directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5864-5870.
    3. Julie Fournet & Alain Barrat, 2014. "Contact Patterns among High School Students," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-17, September.
    4. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    5. Ingo Scholtes & Nicolas Wider & René Pfitzner & Antonios Garas & Claudio J. Tessone & Frank Schweitzer, 2014. "Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    6. Santo Fortunato, 2004. "UNIVERSALITY OF THE THRESHOLD FOR COMPLETE CONSENSUS FOR THE OPINION DYNAMICS OF DEFFUANTet al," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(09), pages 1301-1307.
    7. Jean-Charles Delvenne & Renaud Lambiotte & Luis E. C. Rocha, 2015. "Diffusion on networked systems is a question of time or structure," Nature Communications, Nature, vol. 6(1), pages 1-10, November.
    8. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    9. Guillaume Deffuant & David Neau & Frederic Amblard & Gérard Weisbuch, 2000. "Mixing beliefs among interacting agents," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 87-98.
    10. Petter Holme, 2015. "Modern temporal network theory: a colloquium," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(9), pages 1-30, September.
    11. Jin, Cheng & Li, Yifu & Jin, Xiaogang, 2017. "Political opinion formation: Initial opinion distribution and individual heterogeneity of tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 257-266.
    12. Hidalgo, Cesar A. & Rodriguez-Sickert, C., 2008. "The dynamics of a mobile phone network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3017-3024.
    13. Génois, Mathieu & Vestergaard, Christian L. & Fournet, Julie & Panisson, André & Bonmarin, Isabelle & Barrat, Alain, 2015. "Data on face-to-face contacts in an office building suggest a low-cost vaccination strategy based on community linkers," Network Science, Cambridge University Press, vol. 3(3), pages 326-347, September.
    14. Benjamin Blonder & Anna Dornhaus, 2011. "Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-8, May.
    15. Weisbuch, Gérard & Deffuant, Guillaume & Amblard, Frédéric, 2005. "Persuasion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 555-575.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Charcon, D.Y. & Monteiro, L.H.A., 2020. "A multi-agent system to predict the outcome of a two-round election," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    2. Rezaei, Vahid & Khanmirza, Esmaeel, 2024. "Continuous-time min-max consensus protocol: A unified approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 218(C), pages 292-310.
    3. Dong Jiang & Qionglin Dai & Haihong Li & Junzhong Yang, 2024. "Opinion dynamics based on social learning theory," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(12), pages 1-9, December.
    4. Wang, Chaoqian, 2021. "Opinion dynamics with bilateral propaganda and unilateral information blockade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).

    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. Huang, Changwei & Dai, Qionglin & Han, Wenchen & Feng, Yuee & Cheng, Hongyan & Li, Haihong, 2018. "Effects of heterogeneous convergence rate on consensus in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 428-435.
    2. Han, Wenchen & Feng, Yuee & Qian, Xiaolan & Yang, Qihui & Huang, Changwei, 2020. "Clusters and the entropy in opinion dynamics on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    3. Teo Victor Silva & Sebastián Gonçalves & Bruno Requião Cunha, 2024. "Bounded confidence opinion dynamics with Asch-like social conformity in complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(9), pages 1-10, September.
    4. Takesue, Hirofumi, 2023. "Relative opinion similarity leads to the emergence of large clusters in opinion formation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    5. Huang, Changwei & Bian, Huanyu & Han, Wenchen, 2024. "Breaking the symmetry neutralizes the extremization under the repulsion and higher order interactions," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    6. 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.
    7. Evangelos Ioannidis & Nikos Varsakelis & Ioannis Antoniou, 2020. "Promoters versus Adversaries of Change: Agent-Based Modeling of Organizational Conflict in Co-Evolving Networks," Mathematics, MDPI, vol. 8(12), pages 1-25, December.
    8. 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.
    9. Shang, Yilun, 2018. "Hybrid consensus for averager–copier–voter networks with non-rational agents," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 244-251.
    10. Aming Li & Yang-Yu Liu, 2020. "Controlling Network Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(07n08), pages 1-19, February.
    11. 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.
    12. 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.
    13. Ghezelbash, Ehsan & Yazdanpanah, Mohammad Javad & Asadpour, Masoud, 2019. "Polarization in cooperative networks through optimal placement of informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Pedraza, Lucía & Pinasco, Juan Pablo & Saintier, Nicolas & Balenzuela, Pablo, 2021. "An analytical formulation for multidimensional continuous opinion models," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    15. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    16. Dong Jiang & Qionglin Dai & Haihong Li & Junzhong Yang, 2024. "Opinion dynamics based on social learning theory," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(12), pages 1-9, December.
    17. Hendrickx, Julien M., 2008. "Order preservation in a generalized version of Krause’s opinion dynamics model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5255-5262.
    18. Maciel, Marcelo V. & Martins, André C.R., 2020. "Ideologically motivated biases in a multiple issues opinion model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    19. Martins, André C.R., 2022. "Extremism definitions in opinion dynamics models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    20. Chen, Shuwei & Glass, David H. & McCartney, Mark, 2016. "Characteristics of successful opinion leaders in a bounded confidence model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 426-436.

    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:523:y:2019:i:c:p:1355-1370. 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.