Measuring article quality in Wikipedia using the collaboration network

Collaboratively edited articles such as in Wikipedia suffer from well-identified problems regarding their quality, e.g., information accuracy, reputability of third-party sources, vandalism. Due to the huge number of articles and the intensive edit rate, the manual evaluation of article content quality is inconceivable. In this paper, we tackle the problem of automatically establishing the quality of Wikipedia articles. Evidences are shown to consider the interactions between authors and articles to assess the quality score. Collaborations between authors and reviewers are also considered to reinforce the discriminative process. This work gives a generic formulation of the Mutual Reinforcement principle held between articles quality and authors authority and take explicitly advantage of the co-edits graph generated by individuals. Experiments conducted on a set of representative data from Wikipedia show the effectiveness of our approach.