IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-28958-6.html
   My bibliography  Save this article

Transition from simple to complex contagion in collective decision-making

Author

Listed:
  • Nikolaj Horsevad

    (University of Ottawa)

  • David Mateo

    (Kido Dynamics)

  • Robert E. Kooij

    (Delft University of Technology
    The Netherlands Organization for Applied Scientific Research (TNO))

  • Alain Barrat

    (Aix Marseille Univ, Université de Toulon, CNRS, CPT, Turing Center for Living Systems
    Tokyo Tech World Research Hub Initiative (WRHI), Tokyo Institute of Technology)

  • Roland Bouffanais

    (University of Ottawa)

Abstract

How does the spread of behavior affect consensus-based collective decision-making among animals, humans or swarming robots? In prior research, such propagation of behavior on social networks has been found to exhibit a transition from simple contagion—i.e, based on pairwise interactions—to a complex one—i.e., involving social influence and reinforcement. However, this rich phenomenology appears so far limited to threshold-based decision-making processes with binary options. Here, we show theoretically, and experimentally with a multi-robot system, that such a transition from simple to complex contagion can also be observed in an archetypal model of distributed decision-making devoid of any thresholds or nonlinearities. Specifically, we uncover two key results: the nature of the contagion—simple or complex—is tightly related to the intrinsic pace of the behavior that is spreading, and the network topology strongly influences the effectiveness of the behavioral transmission in ways that are reminiscent of threshold-based models. These results offer new directions for the empirical exploration of behavioral contagions in groups, and have significant ramifications for the design of cooperative and networked robot systems.

Suggested Citation

  • Nikolaj Horsevad & David Mateo & Robert E. Kooij & Alain Barrat & Roland Bouffanais, 2022. "Transition from simple to complex contagion in collective decision-making," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28958-6
    DOI: 10.1038/s41467-022-28958-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-28958-6
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-28958-6?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Baumann, Fabian & Sokolov, Igor M. & Tyloo, Melvyn, 2020. "A Laplacian approach to stubborn agents and their role in opinion formation on influence networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    4. James Andreoni & Nikos Nikiforakis & Simon Siegenthaler, 2021. "Predicting social tipping and norm change in controlled experiments," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(16), pages 2014893118-, April.
    5. R. Kinney & P. Crucitti & R. Albert & V. Latora, 2005. "Modeling cascading failures in the North American power grid," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 46(1), pages 101-107, July.
    6. Centola, Damon & Eguíluz, Víctor M. & Macy, Michael W., 2007. "Cascade dynamics of complex propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 449-456.
    7. Liang Li & Máté Nagy & Jacob M. Graving & Joseph Bak-Coleman & Guangming Xie & Iain D. Couzin, 2020. "Vortex phase matching as a strategy for schooling in robots and in fish," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    8. Holme, Petter & Rocha, Luis E. C., 2019. "Impact of misinformation in temporal network epidemiology," Network Science, Cambridge University Press, vol. 7(1), pages 52-69, March.
    9. Iacopo Iacopini & Giovanni Petri & Alain Barrat & Vito Latora, 2019. "Simplicial models of social contagion," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    10. Kooij, Robert E. & Sørensen, Nikolaj Horsevad & Bouffanais, Roland, 2021. "Tuning the clustering coefficient of generalized circulant networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    11. Koç, Yakup & Warnier, Martijn & Mieghem, Piet Van & Kooij, Robert E. & Brazier, Frances M.T., 2014. "The impact of the topology on cascading failures in a power grid model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 169-179.
    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. Ai, Jun & He, Tao & Su, Zhan, 2023. "Identifying influential nodes in complex networks based on resource allocation similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    2. Seyed Mohsen Mirbagheri & Ata Ollah Rafiei Atani & Mohammadreza Parsanejad, 2023. "The Effect of Collective Decision-Making on Productivity: A Structural Equation Modeling," SAGE Open, , vol. 13(4), pages 21582440231, December.
    3. Almiala, Into & Aalto, Henrik & Kuikka, Vesa, 2023. "Influence spreading model for partial breakthrough effects on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Borges, Henrique M. & Vasconcelos, Vítor V. & Pinheiro, Flávio L., 2024. "How social rewiring preferences bridge polarized communities," Chaos, Solitons & Fractals, Elsevier, vol. 180(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. Huan Wang & Chuang Ma & Han-Shuang Chen & Ying-Cheng Lai & Hai-Feng Zhang, 2022. "Full reconstruction of simplicial complexes from binary contagion and Ising data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Luca Gallo & Lucas Lacasa & Vito Latora & Federico Battiston, 2024. "Higher-order correlations reveal complex memory in temporal hypergraphs," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    3. Daniel Reisinger & Fabian Tschofenig & Raven Adam & Marie Lisa Kogler & Manfred Füllsack & Fabian Veider & Georg Jäger, 2024. "Patterns of stability in complex contagions," Journal of Computational Social Science, Springer, vol. 7(2), pages 1895-1911, October.
    4. Wang, Xuhui & Wu, Jiao & Yang, Zheng & Xu, Kesheng & Wang, Zhengling & Zheng, Muhua, 2024. "The correlation between independent edge and triangle degrees promote the explosive information spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    5. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2022. "Homophily in competing behavior spreading among the heterogeneous population with higher-order interactions," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    6. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    7. Cui, Yajuan & Wei, Ruichen & Tian, Yang & Tian, Hui & Zhu, Xuzhen, 2022. "Information propagation influenced by individual fashion-passion trend on multi-layer weighted network," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    8. Wang, Xiangrong & Koç, Yakup & Derrible, Sybil & Ahmad, Sk Nasir & Pino, Willem J.A. & Kooij, Robert E., 2017. "Multi-criteria robustness analysis of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 19-31.
    9. Lucas Cuadra & Sancho Salcedo-Sanz & Javier Del Ser & Silvia Jiménez-Fernández & Zong Woo Geem, 2015. "A Critical Review of Robustness in Power Grids Using Complex Networks Concepts," Energies, MDPI, vol. 8(9), pages 1-55, August.
    10. Koç, Yakup & Warnier, Martijn & Van Mieghem, Piet & Kooij, Robert E. & Brazier, Frances M.T., 2014. "A topological investigation of phase transitions of cascading failures in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 273-284.
    11. Bompard, Ettore & Napoli, Roberto & Xue, Fei, 2009. "Analysis of structural vulnerabilities in power transmission grids," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(1), pages 5-12.
    12. Yuanzhao Zhang & Maxime Lucas & Federico Battiston, 2023. "Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    13. Champagne, Claudia, 2014. "The international syndicated loan market network: An “unholy trinity”?," Global Finance Journal, Elsevier, vol. 25(2), pages 148-168.
    14. Carattini, Stefano & Gillingham, Kenneth & Meng, Xiangyu & Yoeli, Erez, 2024. "Peer-to-peer solar and social rewards: Evidence from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 340-370.
    15. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    16. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    17. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    18. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    19. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    20. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28958-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.