Measuring article quality in wikipedia: models and evaluation

  • Authors:

  • Meiqun Hu;Ee-Peng Lim;Aixin Sun;Hady Wirawan Lauw;Ba-Quy Vuong

  • Affiliations:

  • Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore

  • Venue:
  • Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
  • Year:
  • 2007

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Abstract

Wikipedia 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.