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Competing for Influence in Networks through Strategic Targeting

Author

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  • Comola, Margherita

    (Paris School of Economics)

  • Rusinowska, Agnieszka

    (Paris School of Economics)

  • Villeval, Marie Claire

    (CNRS, GATE)

Abstract

We experimentally investigate how players with opposing views compete for influence through strategic targeting in networks. We varied the network structure, the relative influence of the opponent, and the heterogeneity of the nodes' initial opinions. Although most players adopted a best-response strategy based on their relative influence, we also observed behaviors deviating from this strategy, such as the tendency to target central nodes and avoid nodes targeted by the opponent. Targeting is also affected by affinity and opposition biases, the strength of which depends on the distribution of initial opinions.

Suggested Citation

  • Comola, Margherita & Rusinowska, Agnieszka & Villeval, Marie Claire, 2024. "Competing for Influence in Networks through Strategic Targeting," IZA Discussion Papers 17315, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp17315
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    as
    1. Rosenkranz, Stephanie & Weitzel, Utz, 2012. "Network structure and strategic investments: An experimental analysis," Games and Economic Behavior, Elsevier, vol. 75(2), pages 898-920.
    2. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    3. Gary Charness & Francesco Feri & Miguel A. Meléndez‐Jiménez & Matthias Sutter, 2014. "Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection," Econometrica, Econometric Society, vol. 82(5), pages 1615-1670, September.
    4. de Vos, Wout & Borm, Peter & Hamers, Herbert, 2023. "Influencing Opinion Networks - Optimization and Games," Other publications TiSEM 6d555d3d-5f45-42e7-8b71-c, Tilburg University, School of Economics and Management.
    5. Currarini, Sergio & Mengel, Friederike, 2016. "Identity, homophily and in-group bias," European Economic Review, Elsevier, vol. 90(C), pages 40-55.
    6. Bloch, Francis & Shabayek, Shaden, 2023. "Targeting in social networks with anonymized information," Games and Economic Behavior, Elsevier, vol. 141(C), pages 380-402.
    7. Subhasish Chowdhury & Dan Kovenock & Roman Sheremeta, 2013. "An experimental investigation of Colonel Blotto games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(3), pages 833-861, April.
    8. 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.
    9. Benjamin Golub & Matthew O. Jackson, 2012. "How Homophily Affects the Speed of Learning and Best-Response Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1287-1338.
    10. Michael D. König & Xiaodong Liu & Yves Zenou, 2019. "R&D Networks: Theory, Empirics, and Policy Implications," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 476-491, July.
    11. Rusinowska, Agnieszka & Taalaibekova, Akylai, 2019. "Opinion formation and targeting when persuaders have extreme and centrist opinions," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 9-27.
    12. Benjamin Golub & Matthew O. Jackson, 2010. "Naïve Learning in Social Networks and the Wisdom of Crowds," American Economic Journal: Microeconomics, American Economic Association, vol. 2(1), pages 112-149, February.
    13. Daniel J. Benjamin & James J. Choi & A. Joshua Strickland, 2010. "Social Identity and Preferences," American Economic Review, American Economic Association, vol. 100(4), pages 1913-1928, September.
    14. Andrea Galeotti & Sanjeev Goyal, 2009. "Influencing the influencers: a theory of strategic diffusion," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 509-532, September.
    15. Banerji, A. & Dutta, Bhaskar, 2009. "Local network externalities and market segmentation," International Journal of Industrial Organization, Elsevier, vol. 27(5), pages 605-614, September.
    16. Kostas Bimpikis & Asuman Ozdaglar & Ercan Yildiz, 2016. "Competitive Targeted Advertising Over Networks," Operations Research, INFORMS, vol. 64(3), pages 705-720, June.
    17. Kalyan Chatterjee & Bhaskar Dutta, 2016. "Credibility And Strategic Learning In Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(3), pages 759-786, August.
    18. Kalyan Chatterjee & Bhaskar Dutta, 2016. "Credibility And Strategic Learning In Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 759-786, August.
    19. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
    20. Francis Bloch & Shaden Shabayek, 2023. "Targeting in social networks with anonymized information," PSE-Ecole d'économie de Paris (Postprint) halshs-04208539, HAL.
    21. George A. Akerlof & Rachel E. Kranton, 2000. "Economics and Identity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(3), pages 715-753.
    22. Marcel Fafchamps & Julien Labonne, 2020. "Family Networks and Distributive Politics," Journal of the European Economic Association, European Economic Association, vol. 18(4), pages 1697-1725.
    23. Peter M. DeMarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, and Unidimensional Opinions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(3), pages 909-968.
    24. Youjin Hahn & Asadul Islam & Eleonora Patacchini & Yves Zenou, 2015. "Teams, Organization and Education Outcomes: Evidence from a field experiment in Bangladesh," Monash Economics Working Papers 35-15, Monash University, Department of Economics.
    25. Charroin, Liza, 2023. "Heterogeneity in sequential network formation games," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    26. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    27. Dan Kovenock & Brian Roberson, 2021. "Generalizations of the General Lotto and Colonel Blotto games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 71(3), pages 997-1032, April.
    28. Belhaj, Mohamed & Deroïan, Frédéric, 2019. "Group targeting under networked synergies," Games and Economic Behavior, Elsevier, vol. 118(C), pages 29-46.
    29. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2018. "Strategic Influence in Social Networks," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 29-50, February.
    30. de Vos, Wout & Borm, Peter & Hamers, Herbert, 2023. "Influencing Opinion Networks - Optimization and Games," Discussion Paper 2023-011, Tilburg University, Center for Economic Research.
    31. Roy Chen & Yan Chen, 2011. "The Potential of Social Identity for Equilibrium Selection," American Economic Review, American Economic Association, vol. 101(6), pages 2562-2589, October.
    32. Chen, Yan & Li, Sherry Xin & Liu, Tracy Xiao & Shih, Margaret, 2014. "Which hat to wear? Impact of natural identities on coordination and cooperation," Games and Economic Behavior, Elsevier, vol. 84(C), pages 58-86.
    33. Nichter, Simeon, 2008. "Vote Buying or Turnout Buying? Machine Politics and the Secret Ballot," American Political Science Review, Cambridge University Press, vol. 102(1), pages 19-31, February.
    34. Belhaj, Mohamed & Deroïan, Frédéric & Safi, Shahir, 2023. "Targeting in networks under costly agreements," Games and Economic Behavior, Elsevier, vol. 140(C), pages 154-172.
    35. Sergio Currarini & Matthew O. Jackson & Paolo Pin, 2009. "An Economic Model of Friendship: Homophily, Minorities, and Segregation," Econometrica, Econometric Society, vol. 77(4), pages 1003-1045, July.
    36. , D. & Tessone, Claudio J. & ,, 2014. "Nestedness in networks: A theoretical model and some applications," Theoretical Economics, Econometric Society, vol. 9(3), September.
    37. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.
    38. Brian Roberson, 2006. "The Colonel Blotto game," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 29(1), pages 1-24, September.
    39. Goyal, Sanjeev & Heidari, Hoda & Kearns, Michael, 2019. "Competitive contagion in networks," Games and Economic Behavior, Elsevier, vol. 113(C), pages 58-79.
    40. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    41. He, Simin & Zou, Xinlu, 2024. "Public goods provision in a network formation game," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 104-131.
    42. Bock, Olaf & Baetge, Ingmar & Nicklisch, Andreas, 2014. "hroot: Hamburg Registration and Organization Online Tool," European Economic Review, Elsevier, vol. 71(C), pages 117-120.
    43. Francis Bloch & Shaden Shabayek, 2023. "Targeting in social networks with anonymized information," Post-Print halshs-04208539, HAL.
    44. Arun G. Chandrasekhar & Horacio Larreguy & Juan Pablo Xandri, 2020. "Testing Models of Social Learning on Networks: Evidence From Two Experiments," Econometrica, Econometric Society, vol. 88(1), pages 1-32, January.
    45. Edoardo Gallo & Chang Yan, 2023. "Efficiency and Equilibrium in Network Games: An Experiment," The Review of Economics and Statistics, MIT Press, vol. 105(6), pages 1515-1529, November.
    46. Wout Vos & Peter Borm & Herbert Hamers, 2024. "Influencing Opinion Networks: Optimization and Games," Dynamic Games and Applications, Springer, vol. 14(4), pages 959-980, September.
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    More about this item

    Keywords

    network; influence; targeting; competition; laboratory experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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