Precision CrowdSourcing: Closing the loop to turn information consumers into information contributors

Qian Zhao, Zihong Huang, Max Harper, Loren G Terveen, Joseph A Konstan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We introduce a theoretical framework called precision crowdsourcing whose goal is to help turn online information consumers into information contributors. The framework looks at the timing and nature of the requests made of users and the feedback provided to users with the goal of increasing long-term contribution and engagement in the site or system. We present the results of a field experiment in which almost 3000 users were asked to tag movies (plus a null control group) as we varied the selection of task (popular/obscure), timing of requests (immediate or varying delays), and relational rhetoric (neutral, system reciprocal, other users reciprocal) of the requests. We found that asking increases tags provided overall, though asking generally decreases the provision of unprompted tags. Users were more likely to comply with our request when we asked them to tag obscure movies and when we used reciprocal request rhetoric.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
PublisherAssociation for Computing Machinery
Pages1615-1625
Number of pages11
ISBN (Electronic)9781450335928
DOIs
StatePublished - Feb 27 2016
Event19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States
Duration: Feb 27 2016Mar 2 2016

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
Volume27

Other

Other19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
CountryUnited States
CitySan Francisco
Period2/27/163/2/16

Bibliographical note

Funding Information:
This work was supported by National Science Foundation with awards IIS-0808692, 0964695, 0968483, 1017697 and 1319382 and Google Social Computing Focused Research program.

Keywords

  • Crowdsourcing
  • Online communities
  • Reciprocity

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