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

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  • 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
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    References listed on IDEAS

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    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.

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