Using open source Web editing software (e.g., wiki), online community users can now easily edit, review and publish articles collaboratively. While much useful knowledge can be derived from these articles, content users and critics are often concerned about their qualities. In this paper, we develop two models, namely basic model and peer review model, for measuring the qualities of these articles and the authorities of their contributors. We represent collaboratively edited articles and their contributors in a bipartite graph. While the basic model measures an article’s quality using both the authorities of contributors and the amount of contribution from each contributor, the peer review model extends the former by considering the review aspect of article content. We present results of experiments conducted on some Wikipedia pages and their contributors. Our result show that the two models can effectively determine the articles’ qualities and contributors’ authorities using the collaborative nature of online communities.

This paper presents 3 article quality measurement models for Wikipedia based upon what the authors have termed as the mutual reinforcement principle. This principle proposes that an article has high quality if it is contributed by high authority authors and a contributor is considered to have high authority if they contribute high quality articles. The models presented include the:

1. Naive model - determines the quality of the article based on the number of words it contains. This provides a very simplistic and probably an inaccurate way of measuring quality.
2. Basic model - calculates the article quality by evaluating the authorities of contributors and the amount of contribution made by each user (contribution is measured by number of words added by a user - doesn't include stop words like a, the, is, etc...). I think issues can arise where high quality articles that are based on subjective / human analysis receive poor scores if they are authored by contributors with low ranking authorities. Alternatively, low quality articles could be unfairly tagged as high quality if they have high authority contributors (but not knowledgeable for the subject matter of that article).
3. Peer review model - is based on the assumption that subsequent contributors will review the prior content of the article and decide which parts to add or remove. The content in the article that survives the changes is more or less approved by the current contributor. Word quality is defined as the aggregation of the word's author and reviewers authorities. The article quality is determined by evaluating the authorities of both the contributors and reviewers and the amount of contribution reviewed (number of reviewed words). This model sounds interesting and I would like to see how its results would compare against the judgement of people who subjectively evaluate the quality of Wikipedia articles.

• Naive, basic and peer review model for article quality measurement
• Mutual reinforcement principle
• Contributor & reviewer authority
• PageRank
• TrustRank
• Hypertext Induced Topic Selection (HITS)
• Dampening mechanism