Clustering editors of wikipedia by editor's biases
|Clustering editors of wikipedia by editor's biases|
|Author(s)||Nakamura A., Suzuki Y., Ishikawa Y.|
|Published in||Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013|
|Keyword(s)||Bias, Edit histories, Peer reviews, Wikipedia (Extra: Bias, Experimental evaluation, Peer review, Wikipedia, Social networking (online))|
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Clustering editors of wikipedia by editor's biases is a 2013 conference paper written in English by Nakamura A., Suzuki Y., Ishikawa Y. and published in Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013.
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, we propose a method of clustering editors by editors' biases for the purpose that we 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. Our system makes use of the relationships between editors: agreement and disagreement. We assume that editors leave texts written by editors that they agree with, and delete texts written by editors that they disagree with. In addition, we 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, we verify that our proposed method is useful in clustering editors by biases. Additionally, we validate that considering the dependency between editors improves the clustering performance.
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