IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2010.01018.html
   My bibliography  Save this paper

Debunking Rumors in Networks

Author

Listed:
  • Luca P. Merlino
  • Paolo Pin
  • Nicole Tabasso

Abstract

We study the diffusion of a true and a false message (the rumor) in a social network. Upon hearing a message, individuals may believe it, disbelieve it, or debunk it through costly verification. Whenever the truth survives in steady state, so does the rumor. Communication intensity in itself is irrelevant for relative rumor prevalence, and the effect of homophily depends on the exact verification process and equilibrium verification rates. Our model highlights that successful policies in the fight against rumors increase individuals' incentives to verify.

Suggested Citation

  • Luca P. Merlino & Paolo Pin & Nicole Tabasso, 2020. "Debunking Rumors in Networks," Papers 2010.01018, arXiv.org, revised May 2022.
  • Handle: RePEc:arx:papers:2010.01018
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2010.01018
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jeanne Hagenbach & Frédéric Koessler, 2010. "Strategic Communication Networks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(3), pages 1072-1099.
    2. Goyal, Sanjeev & Vigier, Adrien, 2015. "Interaction, protection and epidemics," Journal of Public Economics, Elsevier, vol. 125(C), pages 64-69.
    3. Jackson Matthew O. & Rogers Brian W., 2007. "Relating Network Structure to Diffusion Properties through Stochastic Dominance," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 7(1), pages 1-16, February.
    4. Francis Bloch & Gabrielle Demange & Rachel Kranton, 2018. "Rumors And Social Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 421-448, May.
    5. Tabasso, Nicole, 2019. "Diffusion of multiple information: On information resilience and the power of segregation," Games and Economic Behavior, Elsevier, vol. 118(C), pages 219-240.
    6. Porter, Ethan & Wood, Thomas J. & Kirby, David, 2018. "Sex Trafficking, Russian Infiltration, Birth Certificates, and Pedophilia: A Survey Experiment Correcting Fake News," Journal of Experimental Political Science, Cambridge University Press, vol. 5(2), pages 159-164, July.
    7. Halberstam, Yosh & Knight, Brian, 2016. "Homophily, group size, and the diffusion of political information in social networks: Evidence from Twitter," Journal of Public Economics, Elsevier, vol. 143(C), pages 73-88.
    8. Foerster, Manuel, 2019. "Dynamics of strategic information transmission in social networks," Theoretical Economics, Econometric Society, vol. 14(1), January.
    9. Akbarpour, Mohammad & Malladi, Suraj & Saberi, Amin, 2018. "Just a Few Seeds More: Value of Network Information for Diffusion," Research Papers 3678, Stanford University, Graduate School of Business.
    10. Talamàs, Eduard & Vohra, Rakesh, 2020. "Free and perfectly safe but only partially effective vaccines can harm everyone," Games and Economic Behavior, Elsevier, vol. 122(C), pages 277-289.
    11. Markus Kinateder & Luca Paolo Merlino, 2017. "Public Goods in Endogenous Networks," American Economic Journal: Microeconomics, American Economic Association, vol. 9(3), pages 187-212, August.
    12. Pooya Molavi & Alireza Tahbaz‐Salehi & Ali Jadbabaie, 2018. "A Theory of Non‐Bayesian Social Learning," Econometrica, Econometric Society, vol. 86(2), pages 445-490, March.
    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. Tuval Danenberg & Drew Fudenberg, 2024. "Endogenous Attention and the Spread of False News," Papers 2406.11024, arXiv.org.

    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. Tabasso, Nicole, 2019. "Diffusion of multiple information: On information resilience and the power of segregation," Games and Economic Behavior, Elsevier, vol. 118(C), pages 219-240.
    2. Bouveret, Géraldine & Mandel, Antoine, 2021. "Social interactions and the prophylaxis of SI epidemics on networks," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    3. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    4. Migrow, Dimitri, 2021. "Designing communication hierarchies," Journal of Economic Theory, Elsevier, vol. 198(C).
    5. Geraldine Bouveret & Antoine Mandel, 2020. "Prophylaxis of Epidemic Spreading with Transient Dynamics," Papers 2007.07580, arXiv.org.
    6. Luca Paolo Merlino & Nicole Tabasso, 2022. "Optimal Verification of Rumors in Networks," Papers 2207.01830, arXiv.org, revised Jun 2024.
    7. Michel Grabisch & Agnieszka Rusinowska & Xavier Venel, 2019. "Diffusion in countably infinite networks," Documents de travail du Centre d'Economie de la Sorbonne 19017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. Ozan Candogan & Nicole Immorlica & Bar Light & Jerry Anunrojwong, 2022. "Social Learning under Platform Influence: Consensus and Persistent Disagreement," Papers 2202.12453, arXiv.org, revised Oct 2023.
    9. Gieczewski, Germán, 2022. "Verifiable communication on networks," Journal of Economic Theory, Elsevier, vol. 204(C).
    10. Cerdeiro, Diego A., 2017. "Contagion exposure and protection technology," Games and Economic Behavior, Elsevier, vol. 105(C), pages 230-254.
    11. Ascensión Andina-Díaz & José A. García-Martínez & Antonio Parravano, 2019. "The market for scoops: a dynamic approach," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 175-206, June.
    12. Matteo Bizzarri & Fabrizio Panebianco & Paolo Pin, 2023. "Homophily and Infections: Static and Dynamic Effects," CSEF Working Papers 672, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    13. Ding, Sihua, 2022. "Link investment substitutability: A factor influencing network formation," Games and Economic Behavior, Elsevier, vol. 136(C), pages 340-359.
    14. Adriani, Fabrizio & Ladley, Dan, 2021. "Social distance, speed of containment and crowding in/out in a network model of contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 597-625.
    15. Sebastiano Della Lena & Luca Paolo Merlino, 2021. "Group Identity, Social Learning and Opinion Dynamics," Papers 2110.07226, arXiv.org, revised May 2022.
    16. Andrea Galeotti & Brian W. Rogers, 2013. "Strategic Immunization and Group Structure," American Economic Journal: Microeconomics, American Economic Association, vol. 5(2), pages 1-32, May.
    17. Nizar Allouch, 2017. "Aggregation in Networks," Studies in Economics 1718, School of Economics, University of Kent.
    18. Nicole Tabasso, 2014. "Diffusion of Multiple Information," School of Economics Discussion Papers 0914, School of Economics, University of Surrey.
    19. Robbett, Andrea & Matthews, Peter Hans, 2018. "Partisan bias and expressive voting," Journal of Public Economics, Elsevier, vol. 157(C), pages 107-120.
    20. Marco Manacorda & Guido Tabellini & Andrea Tesei, 2022. "Mobile internet and the rise of political tribalism in Europe," CEP Discussion Papers dp1877, Centre for Economic Performance, LSE.

    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2010.01018. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.