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Automatically Evaluating the Quality of Contents Created in Collaborative Knowledge Building
Abstract
Using wikis, with minimum planning, significant projects can be accomplished almost effortlessly by collaborative knowledge building through continuous contributions from caring community members. Since any registered member can change the content of a wiki page at any time, how to enhance the quality of a wiki becomes a pressing issue. This paper reports a pilot study of identifying factors that can enhance the quality of contents built by open collaborative knowledge building. Using stepwise discriminant analysis and logistic regression, several variables were successfully identified that could contribute positively to the high quality of wiki pages. The result was analyzed using Receiver Operating Characteristic (ROC) curves from signal detection theory. The predictor worked remarkably well and was promising, with a high detection rate and a low false-alarm rate. The finding can help programmers and architects of open collaborative knowledge building systems to design and implement mechanisms that will facilitate high quality content creations.
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