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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (6): 83-92    DOI: 10.11925/infotech.2096-3467.2017.06.09
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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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[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.

Key wordsCredibility Degree Measure      Web Content      Bayesian Theory      Social Media      Collective Intelligence     
Received: 22 February 2017      Published: 25 August 2017
ZTFLH:  G2  

Cite this article:

Li Baozhen,Wang Ya,Zhou Ke. Measuring Credibility of Social Media Contents Based on Bayesian Theory. Data Analysis and Knowledge Discovery, 2017, 1(6): 83-92.

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