| Summary: | A social network service (SNS) is a platform to build social networks or social relations among people. Many users enjoy SNS with their smart devices, which are mostly equipped with sensory devices. The sensitive information produced by these sensory devices is uploaded to SNS, which may raise many potential risks. In order to share one's sensitive data with random people without security and privacy concerns, this paper proposes a shared interest discovery model for coauthor relationship in SNS, named as coauthor topic (coAT) model, to identify the users with similar interests from social networks, and collapsed Gibbs sampling method is utilized for inferring model parameters. Thus, one can reduce the possibility that recommended users are not friends but attackers. Finally, extensive experimental results on NIPS dataset indicate that our coAT model is feasible and efficient.
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