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Measuring article quality in Wikipedia: models and evaluation
Abstract Wikipedia has grown to be the world largesWikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. Despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of Wikipedia articles edited by non-experts and inexperienced contributors. In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. Our basic model is designed based on the mutual dependency between article quality and their author authority. The PeerReview model introduces the review behavior into measuring article quality. Finally, our ProbReview models extend PeerReview with partial reviewership of contributors as they edit various portions of the articles. We conduct experiments on a set of well-labeled Wikipedia articles to evaluate the effectiveness of our quality measurement models in resembling human judgement.ment models in resembling human judgement.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Comments The models were able to properly assess the quality of articles on Wikipedia
Conclusion In this paper, we study models for automatIn this paper, we study models for automatically deriving Wikipedia article quality rankings based on the interaction data between articles and their contributors. Our PeerReview model, which was first proposed in [17], had already shown promising performance over the baseline model Na¨ıve. We further extended it to emulate the probability of article content being reviewed by each contributor. As shown in our experiments, the extended ProbReview models with review probability decaying schemes were the best performers compared with all other models under the same setting. By observing that, user interaction data itself is not sufficient in judging article quality and article length appears to have some merits in identifying quality articles, we incorporated article length 251into article quality measurement. Our experimental results showed some performance improvement by Hybrid Basic and hybrid PeerReview models at γ = 0.1 and γ = 0.2 respectively. However, ProbReview models, did not benefit from article length.odels, did not benefit from article length.
Conference location Lisboa, Portugal +
Data source Experiment responses  + , Wikipedia pages  +
Dates 6-9 +
Doi 10.1145/1321440.1321476 +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Measuring%2Barticle%2Bquality%2Bin%2BWikipedia%3A%2Bmodels%2Band%2Bevaluation%22  +
Has author Meiqun Hu + , Ee-Peng Lim + , Aixin Sun + , Hady Wirawan Lauw + , Ba-Quy Vuong +
Has domain Computer science +
Has topic Computational estimation of trustworthiness +
Month November  +
Pages 243-252  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in CIKM '07 Proceedings of the sixteenth ACM conference on Conference on information and knowledge management +
Publisher Association for Computing Machinery +
Research design Experiment  +
Research questions In this paper, we investigate the problem In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history.ors derived from the article edit history.
Revid 10,866  +
Theories Undetermined
Theory type Design and action  +
Title Measuring article quality in Wikipedia: models and evaluation
Unit of analysis Article  +
Url http://dl.acm.org/citation.cfm?id=1321476  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Live Wikipedia  +
Wikipedia language English  +
Wikipedia page type Article  + , History  + , Discussion and Q&A  +
Year 2007  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:29:35  +
Categories Computational estimation of trustworthiness  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:29:36  +
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