IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v15y2023i3p92-d1081940.html
   My bibliography  Save this article

A Game Theory-Based Model for the Dissemination of Privacy Information in Online Social Networks

Author

Listed:
  • Jingsha He

    (Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China)

  • Yue Li

    (Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China)

  • Nafei Zhu

    (Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China)

Abstract

Online social networks (OSNs) have experienced rapid growth in recent years, and an increasing number of people now use OSNs, such as Facebook and Twitter, to share and spread information on a daily basis. As a special type of information, user personal information is also widely disseminated in such networks, posing threats to user privacy. The study on privacy information dissemination is thus useful for the development of mechanisms and tools for the effective protection of privacy information in OSNs. In this paper, we propose to apply the game theory to establish a sender–receiver game model and the Nash equilibrium to describe the behavioral strategies of users in disseminating privacy information. Factors that affect the dissemination of privacy information are also analyzed with two important aspects: intimacy and popularity of the privacy-concerning subject. Simulation experiments were conducted based on real data sets from scale-free networks and real social networks to compare and analyze the effectiveness of the model. Results show that the proposed game theory is applicable to the privacy information dissemination model, which implements intimacy and popularity in the modeling of the dissemination of privacy information in OSNs. Both the impact of the macro-level OSNs and the micro-relationships between users are evaluated on the dissemination of privacy information, which provides a new perspective for exploring the dissemination of privacy information and facilitates the development of effective mechanisms for privacy protection in OSNs.

Suggested Citation

  • Jingsha He & Yue Li & Nafei Zhu, 2023. "A Game Theory-Based Model for the Dissemination of Privacy Information in Online Social Networks," Future Internet, MDPI, vol. 15(3), pages 1-17, February.
  • Handle: RePEc:gam:jftint:v:15:y:2023:i:3:p:92-:d:1081940
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/15/3/92/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/15/3/92/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    2. Joseph Kwame Adjei & Samuel Adams & Isaac Kofi Mensah & Peter Ebo Tobbin & Solomon Odei-Appiah, 2020. "Digital Identity Management on Social Media: Exploring the Factors That Influence Personal Information Disclosure on Social Media," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
    3. Patrick Hartmann & Paula Fernández & Vanessa Apaolaza & Martin Eisend & Clare D’Souza, 2021. "Explaining Viral CSR Message Propagation in Social Media: The Role of Normative Influences," Journal of Business Ethics, Springer, vol. 173(2), pages 365-385, October.
    4. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, April.
    5. Zhou, Mingyang & He, Xingsheng & Fu, Zhongqian & Zhuo, Zhao, 2016. "Role extraction in complex networks and its application in control of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 458-466.
    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. Adedamola Adesokan & Rowan Kinney & Eirini Eleni Tsiropoulou, 2024. "CROWDMATCH: Optimizing Crowdsourcing Matching through the Integration of Matching Theory and Coalition Games," Future Internet, MDPI, vol. 16(2), pages 1-16, February.

    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. Battigalli, Pierpaolo & Bonanno, Giacomo, 1997. "The Logic of Belief Persistence," Economics and Philosophy, Cambridge University Press, vol. 13(1), pages 39-59, April.
    2. Szabó, György & Borsos, István & Szombati, Edit, 2019. "Games, graphs and Kirchhoff laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 416-423.
    3. 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.
    4. Shi, Yi & Deng, Yawen & Wang, Guoan & Xu, Jiuping, 2020. "Stackelberg equilibrium-based eco-economic approach for sustainable development of kitchen waste disposal with subsidy policy: A case study from China," Energy, Elsevier, vol. 196(C).
    5. Marc Le Menestrel, 2003. "A one-shot Prisoners’ Dilemma with procedural utility," Economics Working Papers 819, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Cheng‐Kuang Wu & Yi‐Ming Chen & Dachrahn Wu & Ching‐Lin Chi, 2020. "A Game Theory Approach for Assessment of Risk and Deployment of Police Patrols in Response to Criminal Activity in San Francisco," Risk Analysis, John Wiley & Sons, vol. 40(3), pages 534-549, March.
    7. Nasimeh Heydaribeni & Achilleas Anastasopoulos, 2019. "Linear Equilibria for Dynamic LQG Games with Asymmetric Information and Dependent Types," Papers 1909.04834, arXiv.org.
    8. Müller, Christoph, 2020. "Robust implementation in weakly perfect Bayesian strategies," Journal of Economic Theory, Elsevier, vol. 189(C).
    9. 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).
    10. Hitoshi Matsushima, 2019. "Implementation without expected utility: ex-post verifiability," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(4), pages 575-585, December.
    11. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    12. Dasgupta Utteeyo, 2011. "Are Entry Threats Always Credible?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(1), pages 1-41, December.
    13. Baran Han, 2018. "The role and welfare rationale of secondary sanctions: A theory and a case study of the US sanctions targeting Iran," Conflict Management and Peace Science, Peace Science Society (International), vol. 35(5), pages 474-502, September.
    14. 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.
    15. Carlos Pimienta & Jianfei Shen, 2014. "On the equivalence between (quasi-)perfect and sequential equilibria," International Journal of Game Theory, Springer;Game Theory Society, vol. 43(2), pages 395-402, May.
    16. Asheim, Geir & Søvik, Ylva, 2003. "The semantics of preference-based belief operators," Memorandum 05/2003, Oslo University, Department of Economics.
    17. Salvador Barberà & Anke Gerber, 2024. "On the Endogenous Order of Play in Sequential Games," Working Papers 1443, Barcelona School of Economics.
    18. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    19. repec:dau:papers:123456789/6818 is not listed on IDEAS
    20. Tobias Harks & Martin Hoefer & Anja Schedel & Manuel Surek, 2021. "Efficient Black-Box Reductions for Separable Cost Sharing," Mathematics of Operations Research, INFORMS, vol. 46(1), pages 134-158, February.
    21. Karbowski, Adam, 2011. "O kilku modelach samolubnego karania w ekonomii behawioralnej [Evolution of altruism in the light of behavioral economics]," MPRA Paper 69604, University Library of Munich, Germany.

    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:gam:jftint:v:15:y:2023:i:3:p:92-:d:1081940. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.