Difference between revisions of "Clustering Editors of Wikipedia by Editor's Biases"
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| + | {{Infobox work | ||
| + | | title = Clustering Editors of Wikipedia by Editor's Biases | ||
| + | | date = 2013 | ||
| + | | authors = [[Akira Nakamura]]<br />[[Yu Suzuki]]<br />[[Yoshiharu Ishikawa]] | ||
| + | | doi = 10.1109/WI-IAT.2013.50 | ||
| + | | link = http://dl.acm.org/citation.cfm?id=2568766 | ||
| + | | plink = https://www.semanticscholar.org/paper/Clustering-Editors-of-Wikipedia-by-Editor's-Biases-Nakamura-Suzuki/b1890cb12da90d78ed3ceec0e6a7ae93bb6b500f/figure/2 | ||
| + | }} | ||
'''Clustering Editors of Wikipedia by Editor's Biases''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Akira Nakamura]], [[Yu Suzuki]] and [[Yoshiharu Ishikawa]]. | '''Clustering Editors of Wikipedia by Editor's Biases''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Akira Nakamura]], [[Yu Suzuki]] and [[Yoshiharu Ishikawa]]. | ||
== Overview == | == Overview == | ||
Wikipedia is an Internet encyclopedia where any user can edit articles. Because editors act on their own judgments, editors' biases are reflected in edit actions. When editors' biases are reflected in articles, the articles should have low [[credibility]]. However, it is difficult for users to judge which parts in articles have biases. In this paper, authors propose a method of clustering editors by editors' biases for the purpose that authors distinguish texts' biases by using editors' biases and aid users to judge the credibility of each description. If each text is distinguished such as by colors, users can utilize it for the judgments of the text credibility. Authors system makes use of the relationships between editors: agreement and disagreement. Authors assume that editors leave texts written by editors that they agree with, and delete texts written by editors that they disagree with. In addition, authors can consider that editors who agree with each other have similar biases, and editors who disagree with each other have different biases. Hence, the relationships between editors enable to classify editors by biases. In experimental evaluation, authors verify that proposed method is useful in clustering editors by biases. Additionally, authors validate that considering the dependency between editors improves the clustering performance. | Wikipedia is an Internet encyclopedia where any user can edit articles. Because editors act on their own judgments, editors' biases are reflected in edit actions. When editors' biases are reflected in articles, the articles should have low [[credibility]]. However, it is difficult for users to judge which parts in articles have biases. In this paper, authors propose a method of clustering editors by editors' biases for the purpose that authors distinguish texts' biases by using editors' biases and aid users to judge the credibility of each description. If each text is distinguished such as by colors, users can utilize it for the judgments of the text credibility. Authors system makes use of the relationships between editors: agreement and disagreement. Authors assume that editors leave texts written by editors that they agree with, and delete texts written by editors that they disagree with. In addition, authors can consider that editors who agree with each other have similar biases, and editors who disagree with each other have different biases. Hence, the relationships between editors enable to classify editors by biases. In experimental evaluation, authors verify that proposed method is useful in clustering editors by biases. Additionally, authors validate that considering the dependency between editors improves the clustering performance. | ||
Revision as of 09:54, 11 August 2019
Authors | Akira Nakamura Yu Suzuki Yoshiharu Ishikawa |
|---|---|
Publication date | 2013 |
DOI | 10.1109/WI-IAT.2013.50 |
Links | Original Preprint |
Clustering Editors of Wikipedia by Editor's Biases - scientific work related to Wikipedia quality published in 2013, written by Akira Nakamura, Yu Suzuki and Yoshiharu Ishikawa.
Overview
Wikipedia is an Internet encyclopedia where any user can edit articles. Because editors act on their own judgments, editors' biases are reflected in edit actions. When editors' biases are reflected in articles, the articles should have low credibility. However, it is difficult for users to judge which parts in articles have biases. In this paper, authors propose a method of clustering editors by editors' biases for the purpose that authors distinguish texts' biases by using editors' biases and aid users to judge the credibility of each description. If each text is distinguished such as by colors, users can utilize it for the judgments of the text credibility. Authors system makes use of the relationships between editors: agreement and disagreement. Authors assume that editors leave texts written by editors that they agree with, and delete texts written by editors that they disagree with. In addition, authors can consider that editors who agree with each other have similar biases, and editors who disagree with each other have different biases. Hence, the relationships between editors enable to classify editors by biases. In experimental evaluation, authors verify that proposed method is useful in clustering editors by biases. Additionally, authors validate that considering the dependency between editors improves the clustering performance.
