IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v17y2011i2d10.1007_s10588-011-9085-7.html
   My bibliography  Save this article

The influence of random interactions and decision heuristics on norm evolution in social networks

Author

Listed:
  • Declan Mungovan

    (National University of Ireland)

  • Enda Howley

    (National University of Ireland)

  • Jim Duggan

    (National University of Ireland)

Abstract

In this paper we explore the effect that random social interactions have on the emergence and evolution of social norms in a simulated population of agents. In our model agents observe the behaviour of others and update their norms based on these observations. An agent’s norm is influenced by both their own fixed social network plus a second random network that is composed of a subset of the remaining population. Random interactions are based on a weighted selection algorithm that uses an individual’s path distance on the network to determine their chance of meeting a stranger. This means that friends-of-friends are more likely to randomly interact with one another than agents with a higher degree of separation. We then contrast the cases where agents make highest utility based rational decisions about which norm to adopt versus using a Markov Decision process that associates a weight with the best choice. Finally we examine the effect that these random interactions have on the evolution of a more complex social norm as it propagates throughout the population. We discover that increasing the frequency and weighting of random interactions results in higher levels of norm convergence and in a quicker time when agents have the choice between two competing alternatives. This can be attributed to more information passing through the population thereby allowing for quicker convergence. When the norm is allowed to evolve we observe both global consensus formation and group splintering depending on the cognitive agent model used.

Suggested Citation

  • Declan Mungovan & Enda Howley & Jim Duggan, 2011. "The influence of random interactions and decision heuristics on norm evolution in social networks," Computational and Mathematical Organization Theory, Springer, vol. 17(2), pages 152-178, May.
    • Handle: RePEc:spr:comaot:v:17:y:2011:i:2:d:10.1007_s10588-011-9085-7
    DOI: 10.1007/s10588-011-9085-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-011-9085-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-011-9085-7?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. F. Benjamin Zhan & Charles E. Noon, 1998. "Shortest Path Algorithms: An Evaluation Using Real Road Networks," Transportation Science, INFORMS, vol. 32(1), pages 65-73, February.
    2. Christos H. Papadimitriou & John N. Tsitsiklis, 1987. "The Complexity of Markov Decision Processes," Mathematics of Operations Research, INFORMS, vol. 12(3), pages 441-450, August.
    3. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    4. Joel A. C. Baum & Andrew V. Shipilov & Tim J. Rowley, 2003. "Where do small worlds come from?," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 12(4), pages 697-725, August.
    5. Eocman Lee & Jeho Lee & Jongseok Lee, 2006. "Reconsideration of the Winner-Take-All Hypothesis: Complex Networks and Local Bias," Management Science, INFORMS, vol. 52(12), pages 1838-1848, December.
    6. White, Chelsea C. & White, Douglas J., 1989. "Markov decision processes," European Journal of Operational Research, Elsevier, vol. 39(1), pages 1-16, March.
    7. Elinor Ostrom, 2000. "Collective Action and the Evolution of Social Norms," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 137-158, Summer.
    8. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    9. Goldfarb, Brent & Henrekson, Magnus, 2003. "Bottom-up versus top-down policies towards the commercialization of university intellectual property," Research Policy, Elsevier, vol. 32(4), pages 639-658, April.
    10. Christine Horne, 2007. "Explaining Norm Enforcement," Rationality and Society, , vol. 19(2), pages 139-170, May.
    11. Kathleen M. Carley, 2009. "Computational modeling for reasoning about the social behavior of humans," Computational and Mathematical Organization Theory, Springer, vol. 15(1), pages 47-59, March.
    12. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    13. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    14. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
    15. Fabiola López y López & Michael Luck & Mark d’Inverno, 2006. "A normative framework for agent-based systems," Computational and Mathematical Organization Theory, Springer, vol. 12(2), pages 227-250, October.
    16. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
    17. Gary Mckeown & Noel Sheehy, 2006. "Mass Media and Polarisation Processes in the Bounded Confidence Model of Opinion Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-11.
    18. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    19. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
    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. Davide Secchi & Raffaello Seri, 2017. "Controlling for false negatives in agent-based models: a review of power analysis in organizational research," Computational and Mathematical Organization Theory, Springer, vol. 23(1), pages 94-121, March.
    2. Raúl M. Ortiz-Gaona & Marcos Postigo-Boix & José L. Melús-Moreno, 2021. "Extent prediction of the information and influence propagation in online social networks," Computational and Mathematical Organization Theory, Springer, vol. 27(2), pages 195-230, June.
    3. Luis Almeida Costa & João Amaro Matos, 2014. "Attitude change in arbitrarily large organizations," Computational and Mathematical Organization Theory, Springer, vol. 20(3), pages 219-251, September.

    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. Dong, Bin & Dulleck, Uwe & Torgler, Benno, 2012. "Conditional corruption," Journal of Economic Psychology, Elsevier, vol. 33(3), pages 609-627.
    2. Agranov, Marina & Elliott, Matt & Ortoleva, Pietro, 2021. "The importance of Social Norms against Strategic Effects: The case of Covid-19 vaccine uptake," Economics Letters, Elsevier, vol. 206(C).
    3. López-Pintado, Dunia, 2012. "Influence networks," Games and Economic Behavior, Elsevier, vol. 75(2), pages 776-787.
    4. Rubin, Jared, 2014. "Centralized institutions and cascades," Journal of Comparative Economics, Elsevier, vol. 42(2), pages 340-357.
    5. Michael J. Prietula & Daniel Conway, 2009. "The evolution of metanorms: quis custodiet ipsos custodes?," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 147-168, September.
    6. Ray M. Chang & Wonseok Oh & Alain Pinsonneault & Dowan Kwon, 2010. "A Network Perspective of Digital Competition in Online Advertising Industries: A Simulation-Based Approach," Information Systems Research, INFORMS, vol. 21(3), pages 571-593, September.
    7. Desmarchelier, Benoît & Fang, Eddy S., 2016. "National culture and innovation diffusion. Exploratory insights from agent-based modeling," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 121-128.
    8. Tuan Q. Phan & David Godes, 2018. "The Evolution of Influence Through Endogenous Link Formation," Marketing Science, INFORMS, vol. 37(2), pages 259-278, March.
    9. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    10. Wang, Peiwen & Chen, Minghua & Wu, Ji & Yan, Yuanyun, 2023. "Do peer effects matter in bank risk? Some cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    11. Davide Crapis & Bar Ifrach & Costis Maglaras & Marco Scarsini, 2017. "Monopoly Pricing in the Presence of Social Learning," Management Science, INFORMS, vol. 63(11), pages 3586-3608, November.
    12. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    13. Feri, Francesco & Meléndez-Jiménez, Miguel A. & Ponti, Giovanni & Vega-Redondo, Fernando, 2011. "Error cascades in observational learning: An experiment on the Chinos game," Games and Economic Behavior, Elsevier, vol. 73(1), pages 136-146, September.
    14. Patrick Hummel & Brian Knight, 2015. "Sequential Or Simultaneous Elections? A Welfare Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(3), pages 851-887, August.
    15. Jonathan E. Alevy & Michael S. Haigh & John List, 2006. "Information Cascades: Evidence from An Experiment with Financial Market Professionals," NBER Working Papers 12767, National Bureau of Economic Research, Inc.
    16. Gong, Zheng & Tian, Feng & Xu, Boyan, 2013. "Limited Information Aggregation and Externalities - A Simple Model of Metastable Market," MPRA Paper 52143, University Library of Munich, Germany.
    17. Pierdzioch, Christian & Reid, Monique B. & Gupta, Rangan, 2016. "Inflation forecasts and forecaster herding: Evidence from South African survey data," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 62(C), pages 42-50.
    18. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    19. Dorothea Kübler & Georg Weizsäcker, 2004. "Limited Depth of Reasoning and Failure of Cascade Formation in the Laboratory," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(2), pages 425-441.
    20. Marco Castillo & Gregory Leo & Ragan Petrie, 2013. "Room Effects," Working Papers 1040, George Mason University, Interdisciplinary Center for Economic Science, revised Apr 2013.

    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:spr:comaot:v:17:y:2011:i:2:d:10.1007_s10588-011-9085-7. 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.springer.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.