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数据分析与知识发现  2017, Vol. 1 Issue (6): 83-92     https://doi.org/10.11925/infotech.2096-3467.2017.06.09
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于贝叶斯理论的社会化媒体网络信息内容可信度测度*
李保珍1(), 王亚2, 周可1
1南京审计大学国家审计大数据研究中心 南京 211815
2江苏科技大学经济管理学院 镇江 212003
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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摘要 

目的】构建网络信息内容可信度的定量测度模型, 以提高虚假信息的筛除效率。【方法】基于贝叶斯推理理论, 构建网络信息内容可信度的测度模型; 基于贝叶斯决策理论, 构建可信度测度有效性的最小错误率评估模型。【结果】基于实际数据集的实验结果表明, 随着社会化媒体参与者规模增加, 可信度测度的最小错误率呈下降趋势, 且贝叶斯可信度测度模型总体优于传统的模糊可信度测度模型。【局限】可信度测度错误率的影响因素只关注参与者规模因素, 而其他影响因素, 如条件属性或可参照对象等, 将需要进一步研究。【结论】基于集体智慧理论, 揭示网络信息内容可信度测度的最小错误率会随着参与者规模增加而降低。

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李保珍
王亚
周可
关键词 可信度测度网络信息内容贝叶斯理论社会化媒体集体智慧    
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.

Key wordsCredibility Degree Measure    Web Content    Bayesian Theory    Social Media    Collective Intelligence
收稿日期: 2017-02-22      出版日期: 2017-08-25
ZTFLH:  G2  
基金资助:*本文系国家自然科学基金项目“多元交互视角下网络信息可信度的场景性测度研究”(项目编号: 71673122)、国家自然科学基金项目“基于编译的嵌入式软件可靠性加强方法研究”(项目编号: 61640220)和全国统计科学研究重点项目“社交媒体环境下统计数据信息可信度的测度研究”(项目编号: 2015LZ29)的研究成果之一
引用本文:   
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.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2017.06.09      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2017/V1/I6/83
  特定对象“苹果”具有属性红或甜的状态文氏图
  计算机领域对象可信度测度的错误率随用户规模变化的趋势
  社交领域对象可信度测度的错误率随用户规模变化的趋势
  网络新闻领域对象可信度测度的错误率随用户规模变化的趋势
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