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| Measuring Credibility of Social Media Contents Based on Bayesian Theory |
Li Baozhen1( ), Wang Ya2, Zhou Ke1 |
1National Audit Big Data Research Center, Nanjing Audit University, Nanjing 211815, China
2School of Science and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China |
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Abstract [Objective] This paper builds a model to quantitatively measure the credibility of Web contents, aiming to improve the efficiency of removing dis-information. [Methods] We first constructed a credibility measurement model based on Bayesian inference theory, and then established a minimum error rate evaluation model for credibility measurement with Bayesian decision theory. [Results] With the increasing of social media users, the minimum error rate of credibility degree went down, and the proposed model had better performance than those based on traditional fuzzy theory. [Limitations] The influencing factors of the reliability measurement model only include the number of participants. More research is needed to examine other factors, such as the conditional attributes and the reference objects. [Conclusions] This paper reveals that the minimum error rate is decreased by increasing the number of participants.
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Received: 22 February 2017
Published: 25 August 2017
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