Credibility Evaluation and PROV Model of Zhihu Information

  • Zhang Ting ,
  • Qi Xianghua
Expand
  • School of Economics and Management, Shanxi University, Taiyuan 030006

Received date: 2018-07-18

  Revised date: 2018-11-14

  Online published: 2019-05-05

Abstract

[Purpose/significance] This paper aims to construct a PROV provenance model and user credibility evaluation index for information dissemination process, quantify the credibility of information, and enrich and improve the method of credibility evaluation of socialized Q&A community platform.[Method/process] The paper analyzed the credibility of the data origination concept assessment information from the perspective of the information dissemination process, traced and recorded the source and dissemination of the information by establishing the relevant PROV data provenance model. The process, combined with the user credibility scores involved in the information dissemination process, was used to calculate the quantitative results of the credibility of the information.[Result/conclusion] Through the evaluation of the credibility of information, the information credibility evaluation method is further improved, which provides a new idea for optimizing the quality of community information.

Cite this article

Zhang Ting , Qi Xianghua . Credibility Evaluation and PROV Model of Zhihu Information[J]. Library and Information Service, 2019 , 63(9) : 85 -94 . DOI: 10.13266/j.issn.0252-3116.2019.09.009

References

[1] 知乎:截至9月份,知乎个人注册用户总数超过了1亿[EB/OL].[2018-12-24].http://www.sohu.com/a/193351816_812860.
[2] CNNIC.第41次中国互联网络发展状况统计报[EB/OL].[2018-01-23].http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201803/P020180305409870339136.pdf.
[3] 曹高辉, 胡紫祎, 张煜轩,等. 基于外部线索的社会化问答平台信息质量感知模型研究[J]. 情报科学, 2016, 34(11):122-128.
[4] 姜雯, 许鑫. 在线问答社区信息质量评价研究综述[J].现代图书情报技术, 2014, 30(6):41-50.
[5] 王平,程齐凯.网络信息可信度评估的研究进展及述评[J].信息资源管理学报,2013,3(01):46-52.
[6] 李保珍,王亚.社交媒体环境下网络信息可信度评估研究综述[J].情报学报,2015,34(12):1314-1321.
[7] JEON J, CROFT W B, LEE J H, et al. A framework to predict the quality of answers with non-textual features[C]//Proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval. New York:ACM Press,2006:228-235.
[8] AGICHTEIN E, CASTILLO C, DONATO D, et al. Finding high-quality content in social media[C]//Proceedings of the 2008 international conference on Web search and Web data mining (WSDM'08). New York:ACM, 2008:183-194.
[9] SHAH C, POMERANTZ J. Evaluating and predicting answer quality in community QA[C]//International ACM SIGIR conference on research and development in information retrieval. New York:ACM, 2010:411-418.
[10] TIAN Q, ZHANG P, LI B. Towards predicting the best answers in community-based question-answering services[EB/OL].[2018-09-15].http//www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/view/6096/6334.
[11] 来社安, 蔡中民. 基于相似度的问答社区问答质量评价方法[J]. 计算机应用与软件, 2013, 30(2):266-269.
[12] 王伟, 冀宇强, 王洪伟,等. 中文问答社区答案质量的评价研究:以知乎为例[J]. 图书情报工作, 2017, 61(22):36-44.
[13] OH S, WORRALL A, YI Y J. Quality evaluation of health answers in Yahoo! Answers:a comparison between experts and users[J].Proceedings of the American Society for Information Science & Technology, 2012, 48(1):1-3.
[14] 贾佳, 宋恩梅, 苏环. 社会化问答平台的答案质量评估——以"知乎"、"百度知道"为例[J]. 信息资源管理学报, 2013, 3(2):19-28.
[15] FICHMAN P. A comparative assessment of answer quality on four question answering sites[J]. Journal of information science, 2011, 37(5):476-486.
[16] KIM S,OH J S,OH S. Best-answer selection criteria in a social Q&A site from the user-oriented relevance perspective[C]//Proceedings of the 70th annual meeting of American Society for Information Science and Technology (ASIST). Silver Spring:American Society for Information Science and Technology, 2007:1-15.
[17] 李晶. 虚拟社区信息质量建模及感知差异性比较研究[D].武汉:武汉大学, 2013.
[18] 孙晓宁, 赵宇翔, 朱庆华. 基于SQA系统的社会化搜索答案质量评价指标构建[J]. 中国图书馆学报, 2015, 41(4):65-82.
[19] 施国良, 陈旭, 杜璐锋. 社会化问答网站答案认可度的影响因素研究——以知乎为例[J]. 现代情报, 2016, 36(6):41-45.
[20] W3C.PROV-O:the PROV ontology[EB/OL].[2018-01-11].http://www.w3.org/TR/2013/REC-prov-o20130430/.
[21] 闫浩.认真的人永远存在:关于知乎,这可能是最真诚的一篇分享了[EB/OL].[2018-03-28].https://www.huxiu.com/article/147187/1.html?f=index_feed_article.
[22] 倪静,孟宪学.关联数据环境下数据溯源描述语言的比较研究[J].现代图书情报技术,2013(2):18-23.
[23] 刘清松. 中文微博信息可信度分析方法研究[D]. 北京:北京信息科技大学, 2015.
[24] 知乎.什么是知乎的"优秀回答者"标识?[EB/OL].[2017-12-23].https://www.zhihu.com/question/48509984.
[25] 倪静, 孟宪学. PROV数据溯源模型及Web应用[J]. 图书情报工作, 2014, 58(3):13-19.
Outlines

/