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NIPS ˙08 Workshop: Beyond Search - Computational Intelligence for the Web

Collective Wisdom: Information Growth in Wikis and Blogs

author: Malik Magdon-Ismail, Rensselaer Polytechnic Institute
coauthor: Sanmay Das, Rensselaer Polytechnic Institute

Description

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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Slides
0:00 Collective Wisdom: Information Growth in Wikis and Blogs
0:34 “The Big Aggregators”
1:50 Motivation (1)
1:52 Motivation (2)
3:00 Motivation (3)
3:24 Motivation (4)
4:19 Questions
4:47 Article Growth in Wikipedia
5:51 Raw Edit Dynamics
6:59 The Model
7:46 Specifying the Model
9:21 Solving the System
10:37 Implications For the Edit Lifecycle
12:51 Wikipedia
14:08 Blogs
15:49 Blog data
16:53 Decay
17:23 Discussion
19:05 Open Questions (1)
19:10 Open Questions (2)
19:49 Open Questions (3)
20:18 Open Questions (4)
20:22 - questions
21:07 - questions

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