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
[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.
李保珍, 王亚, 周可. 基于贝叶斯理论的社会化媒体网络信息内容可信度测度*[J]. 数据分析与知识发现, 2017, 1(6): 83-92.
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.
Metzger M J.Making Sense of Credibility on the Web: Models for Evaluating Online Information and Recommendations for Future Research.[J] Journal of the Association for Information Science and Technology, 2007, 58(13): 2078-2091.
doi: 10.1002/asi.20672
[2]
Fogg B J, Marshall J, Kameda T, et al.Web Credibility Research: A Method for Online Experiments and Early Study Results[C]//Proceedings of CHI’01 Extended Abstracts on Human Factors in Computing Systems. New York, USA: ACM, 2001: 295-296.
[3]
Jaworski W, Rejmund E, Wierzbicki A.Credibility Microscope: Relating Web Page Credibility Evaluations to Their Textual Content[C]//Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies. Washington, USA: IEEE Computer Society, 2014: 297-302.
[4]
Flanagin A J, Metzger M J, Pure R, et al.Mitigating Risk in Ecommerce Transactions: Perceptions of Information Credibility and the Role of User-Generated Ratings in Product Quality and Purchase Intention[J]. Electronic Commerce Research, 2014, 14(1): 1-23.
doi: 10.1007/s10660-014-9139-2
(Liu Bing, Zhang Yaohui.Empirical Study on Information Quality Influencing Factors Based on Network User Experience and Perception[J]. Journal of the China Society for Scientific and Technical Information, 2013, 32(6): 663-672.)
doi: 10.3772/j.issn.1000-0135.2013.06.011
[6]
Castillo C, Mendoza M, Poblete B.Predicting Information Credibility in Time-Sensitive Social Media[J]Internet Research, 2013, 23(5): 560-588.
doi: 10.1108/IntR-05-2012-0095
[7]
Pasternack J, Roth D.Latent Credibility Analysis[C]// Proceedings of International Conference on World Wide Web. 2013: 1009-1020.
[8]
Bartomiej B, Jaworski W, Wierzbicki A.Application of TextRank Algorithm for Credibility Assessment[C]// Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence. Washington, USA: IEEE Computer Society, 2014: 451-454.
[9]
Patra K, Mondal S K.Multi-item Supplier Selection Model with Fuzzy Risk Analysis Studied by Possibility and Necessity Constraints[J]Fuzzy Information & Engineering, 2015, 7(4): 451-474.
doi: 10.1016/j.fiae.2015.11.004
(Zhou Yatong, Zhang Taiyi, Lu Zhaogan.Decision Tree Model Based on Bayesian Inference[J]. Journal of Xi’an Jiao Tong University, 2006, 40(8): 888-891.)
doi: 10.3321/j.issn:0253-987X.2006.08.005
[11]
Lee E S, Li R J.Comparison of Fuzzy Numbers Based on the Probability Measure of Fuzzy Events[J]Computers & Mathematics with Applications, 1988, 15(10): 887-896.
doi: 10.1016/0898-1221(88)90124-1
(Jing Zhong, He Ming.Application of Bayesian Decision Making Based on Minimum Error Rate in Handwritten Chinese Character Recognition[J]. Journal of Liaoning University of Technology: Natural Science Edition, 2009, 29(2): 98-100.)
doi: 10.3969/j.issn.1674-3261.2009.02.009
(Yang Huiyun.Research on Image Denoising Algorithm Based on Minimum Error Rate Bayes Decision and Smoothing Filter[D]. Shijiazhuang: Hebei Normal University, 2010.)
(Zhou Quan, Tang Shukun.Perceived Social Media Source Credibility and Its Influence Factors: An Empirical Analysis Based on Weibo Users’ Convenience Sample Survey[J]. Journalism & Communication, 2015(4): 18-35.)
(Li Yong, Sang Yanyan.Classification Technology and Implementation Method for Web-based Text Data[J]. Journal of the China Society for Scientific and Technical Information, 2002, 21(1): 21-26.)
doi: 10.3969/j.issn.1000-0135.2002.01.005