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A game theory-based trust measurement model for social networks
Yingjie Wang1, Zhipeng Cai2,3, Guisheng Yin2
1School of Computer and Control Engineering, Yantai University, Qingquan Road, Yantai, 244005 China.
Computational Social Networks
|January 23, 2018
Summary
This study introduces a game theory model to measure trust in social networks, enhancing reliability and addressing free-riding with a punishment mechanism.
Area of Science:
- Social Network Analysis
- Game Theory
- Trust Modeling
Background:
- Trust is crucial for online social networks, enabling information sharing among reliable users.
- Modeling trust is complex, requiring consideration of interaction history, user behavior, and recommendations.
- Accurate trust modeling is a key focus for enhancing online social network functionality.
Purpose of the Study:
- To develop a novel game theory-based trust measurement model for social networks.
- To improve the accuracy of trust assessment by incorporating multiple factors.
- To mitigate the free-riding problem within online social networks.
Main Methods:
- A game theory-based model was developed to calculate trust degrees.
- Trust calculation incorporates service reliability, feedback effectiveness, and recommendation credibility.
- A punishment mechanism was introduced to address specific and global trust free-riding.
Main Results:
- The proposed trust measurement model demonstrates effectiveness in assessing user trust.
- The integrated punishment mechanism successfully resolves the free-riding issue.
- The model provides a more accurate and reliable measure of trust in social networks.
Conclusions:
- The developed trust measurement model is proven effective for social networks.
- The game theory-based punishment mechanism offers a robust solution to the free-riding problem.
- This research contributes to more trustworthy and efficient online social network environments.
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