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A game theory-based trust measurement model for social networks

BACKGROUND: In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider inter...

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Detalles Bibliográficos
Autores principales: Wang, Yingjie, Cai, Zhipeng, Yin, Guisheng, Gao, Yang, Tong, Xiangrong, Han, Qilong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749562/
https://www.ncbi.nlm.nih.gov/pubmed/29355232
http://dx.doi.org/10.1186/s40649-016-0027-x
Descripción
Sumario:BACKGROUND: In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. METHODS: We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. RESULTS AND CONCLUSIONS: We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.