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The Influence of Trust Score on Cooperative Behavior

Claudia-Lavinia Ignat 1 Quang-Vinh Dang 1 Valerie Shalin 2
1 COAST - Web Scale Trustworthy Collaborative Service Systems
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
Abstract : The assessment of trust between users is essential for collaboration. General reputation and ID mechanisms may support users’ trust assessment. However, these mechanisms lack sensitivity to pairwise interactions and specific experience such as betrayal over time. Moreover, they place an interpretation burden that does not scale to dynamic, large-scale systems. While several pairwise trust mechanisms have been proposed, no empirical research examines trust score influence on participant behavior. We study the influence of showing a partner trust score and/or ID on participants’ behavior in a small-group collaborative laboratory experiment based on the trust game. We show that trust score availability has the same effect as an ID to improve cooperation as measured by sending behavior and receiver response. Excellent models based on the trust score predict sender behavior and document participant sensitivity to the provision of partner information. Models based on the trust score for recipient behavior have some predictive ability regarding trustworthiness, but suggest the need for more complex functions relating experience to participant response. We conclude that the parameters of a trust score, including pairwise interactions and betrayal, influence the different roles of participants in the trust game differently, but complement traditional ID and have the advantage of scalability.
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Contributor : Quang Vinh Dang <>
Submitted on : Monday, October 21, 2019 - 12:59:46 PM
Last modification on : Friday, October 23, 2020 - 5:03:09 PM
Long-term archiving on: : Wednesday, January 22, 2020 - 1:01:58 PM


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Claudia-Lavinia Ignat, Quang-Vinh Dang, Valerie Shalin. The Influence of Trust Score on Cooperative Behavior. ACM Transactions on Internet Technology, Association for Computing Machinery, 2019, 19 (4), pp.1-22. ⟨10.1145/3329250⟩. ⟨hal-02307981⟩



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