QualityRank: assessing quality of Wikipedia articles by mutually evaluating editors and texts

Y Suzuki, M Yoshikawa - Proceedings of the 23rd ACM conference on …, 2012 - dl.acm.org
Proceedings of the 23rd ACM conference on Hypertext and social media, 2012dl.acm.org
In this paper, we propose a method to identify high-quality Wikipedia articles by mutually
evaluating editors and texts. A major approach for assessing articles using edit history is a
text survival ratio based approach. However, the problem is that many high-quality articles
are identified as low quality, because many vandals delete high-quality texts, then the
survival ratios of high-quality texts are decreased by vandals. Our approach's strongest point
is its resistance to vandalism. Using our method, if we calculate text quality values using …
In this paper, we propose a method to identify high-quality Wikipedia articles by mutually evaluating editors and texts. A major approach for assessing articles using edit history is a text survival ratio based approach. However, the problem is that many high-quality articles are identified as low quality, because many vandals delete high-quality texts, then the survival ratios of high-quality texts are decreased by vandals. Our approach's strongest point is its resistance to vandalism. Using our method, if we calculate text quality values using editor quality values, vandals do not affect any quality values of the other editors, then the accuracy of text quality values should improve. However, the problem is that editor quality values are calculated by text quality values, and text quality values are calculated by editor quality values. To solve this problem, we mutually calculate editor and text quality values until they converge. Using this method, we can calculate a quality value of a text that takes into consideration that of its editors.
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