SuggestBot: using intelligent task routing to help people find work in Wikipedia
|SuggestBot: using intelligent task routing to help people find work in Wikipedia|
|Author(s)||Dan Cosley, Dan Frankowski, Loren Terveen, John Riedl|
|Keyword(s)||online communities, member-maintained communities, Wikipedia, intelligent task routing, recommender systems|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of publications|
Member-maintained communities ask their users to perform tasks the community needs. From Slashdot, to IMDb, to Wikipedia, groups with diverse interests create community-maintained artifacts of lasting value (CALV) that support the group's main purpose and provide value to others. Said communities don't help members find work to do, or do so without regard to individual preferences, such as Slashdot assigning meta-moderation randomly. Yet social science theory suggests that reducing the cost and increasing the personal value of contribution would motivate members to participate more. We present SuggestBot, software that performs intelligent task routing (matching people with tasks) in Wikipedia. SuggestBot uses broadly applicable strategies of text analysis, collaborative filtering, and hyperlink following to recommend tasks. SuggestBot's intelligent task routing increases the number of edits by roughly four times compared to suggesting random articles. Our contributions are: 1) demonstrating the value of intelligent task routing in a real deployment; 2) showing how to do intelligent task routing; and 3) sharing our experience of deploying a tool in Wikipedia, which offered both challenges and opportunities for research.
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.