Using intelligent task routing and contribution review to help communities build artifacts of lasting value

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Using intelligent task routing and contribution review to help communities build artifacts of lasting value
Authors: Daniel Regis Cosley, Dan Frankowski, Loren Terveen, John Riedl [edit item]
Citation: CHI '06 Proceedings of the SIGCHI conference on Human Factors in computing systems  : 1037-1046. 2006.
Publication type: Conference paper
Peer-reviewed: Yes
Database(s):
DOI: 10.1145/1124772.1124928.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Using intelligent task routing and contribution review to help communities build artifacts of lasting value is a publication by Daniel Regis Cosley, Dan Frankowski, Loren Terveen, John Riedl.


[edit] Abstract

Many online communities are emerging that, like Wikipedia, bring people together to build community-maintained artifacts of lasting value (CALVs). Motivating people to contribute is a key problem because the quantity and quality of contributions ultimately determine a CALV's value. We pose two related research questions: 1) How does intelligent task routing---matching people with work---affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions? A field experiment with 197 contributors shows that simple, intelligent task routing algorithms have large effects. We also model the effect of reviewing contributions on the value of CALVs. The model predicts, and experimental data shows, that value grows more slowly with review before acceptance. It also predicts, surprisingly, that a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community.

[edit] Research questions

"We pose two related research questions: 1) How does intelligent task routing---matching people with work---affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions?"

Research details

Topics: Technical infrastructure, Other antecedents of participation [edit item]
Domains: Information systems [edit item]
Theory type: Explanation [edit item]
Wikipedia coverage: Case [edit item]
Theories: "Undetermined" [edit item]
Research design: Experiment, Statistical analysis [edit item]
Data source: Experiment responses, Websites, Wikipedia pages [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Article, User [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: N/A [edit item]

[edit] Conclusion

"A field experiment with 197 contributors shows that simple, intelligent task routing algorithms have large effects. We also model the effect of reviewing contributions on the value of CALVs. The model predicts, and experimental data shows, that value grows more slowly with review before acceptance. It also predicts, surprisingly, that a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community."

[edit] Comments

""We found that value grows more slowly with review before acceptance and a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community." (p. 1037)"


Further notes[edit]

Facts about "Using intelligent task routing and contribution review to help communities build artifacts of lasting value"RDF feed
AbstractMany online communities are emerging that,Many online communities are emerging that, like Wikipedia, bring people together to build community-maintained artifacts of lasting value (CALVs). Motivating people to contribute is a key problem because the quantity and quality of contributions ultimately determine a CALV's value. We pose two related research questions: 1) How does intelligent task routing---matching people with work---affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions? A field experiment with 197 contributors shows that simple, intelligent task routing algorithms have large effects. We also model the effect of reviewing contributions on the value of CALVs. The model predicts, and experimental data shows, that value grows more slowly with review before acceptance. It also predicts, surprisingly, that a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community. they are made available to the community.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
Comments"We found that value grows more slowly with review before acceptance and a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community." (p. 1037)
ConclusionA field experiment with 197 contributors sA field experiment with 197 contributors shows that simple, intelligent task routing algorithms have large effects. We also model the effect of reviewing contributions on the value of CALVs. The model predicts, and experimental data shows, that value grows more slowly with review before acceptance. It also predicts, surprisingly, that a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community. they are made available to the community.
Data sourceExperiment responses +, Websites + and Wikipedia pages +
Doi10.1145/1124772.1124928 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Using%2Bintelligent%2Btask%2Brouting%2Band%2Bcontribution%2Breview%2Bto%2Bhelp%2Bcommunities%2Bbuild%2Bartifacts%2Bof%2Blasting%2Bvalue%22 +
Has authorDaniel Regis Cosley +, Dan Frankowski +, Loren Terveen + and John Riedl +
Has domainInformation systems +
Has topicTechnical infrastructure + and Other antecedents of participation +
Pages1037-1046 +
Peer reviewedYes +
Publication typeConference paper +
Published inCHI '06 Proceedings of the SIGCHI conference on Human Factors in computing systems +
Research designExperiment + and Statistical analysis +
Research questionsWe pose two related research questions: 1) How does intelligent task routing---matching people with work---affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions?
Revid11,025 +
TheoriesUndetermined
Theory typeExplanation +
TitleUsing intelligent task routing and contribution review to help communities build artifacts of lasting value
Unit of analysisArticle + and User +
Urlhttp://dl.acm.org/citation.cfm?id=1124928 +
Wikipedia coverageCase +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageN/A +
Wikipedia page typeArticle +
Year2006 +