Collective Wisdom: Information Growth in Wikis and Blogs

coauthor: Sanmay Das, Rensselaer Polytechnic Institute
author: Malik Magdon-Ismail, Department of Computer Science, Rensselaer Polytechnic Institute
published: Dec. 20, 2008,   recorded: December 2008,   views: 4304


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Wikis and blogs have become enormously successful media for collaborative information creation. Articles and posts accrue information through the asynchronous editing of users who arrive both seeking information and possibly able to contribute information. Most articles stabilize to high quality, trusted sources of information representing the collective wisdom of all the users who edited the article. We propose a model for information growth which relies on two main observations: (i) as an article's quality improves, it attracts visitors at a faster rate (a rich get richer phenomenon); and, simultaneously, (ii) the chances that a new visitor will improve the article drops (there is only so much that can be said about a particular topic). Our model is able to reproduce many features of the edit dynamics observed on Wikipedia and on blogs collected from LiveJournal; in particular, it captures the observed rise in the edit rate, followed by (1/t) decay.

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