Scalable crowd ideation support through data visualization, mining, and structured workflows

Victor Girotto, Erin Walker, Winslow Burleson

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

Abstract

As the size of innovation communities increases, methods of supporting their creativity need to scale as well. Our research proposes the integration of three scalable techniques into a crowd ideation system: 1) data visualization, 2) structured microtask workflows, and 3) data mining, with the goal of supporting users in convergent and divergent ideation processes. In addition, these techniques do not work in isolation, but instead support each other. Our vision is to create a system that intelligently supports users' ideation in a crowd context while maintaining their agency and facilitating exploration and decision-making.

Original languageEnglish (US)
Title of host publicationCSCW 2017 - Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing
PublisherAssociation for Computing Machinery, Inc
Pages183-186
Number of pages4
ISBN (Electronic)9781450346887
DOIs
StatePublished - Feb 25 2017
Event2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017 - Portland, United States
Duration: Feb 25 2017Mar 1 2017

Other

Other2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2017
CountryUnited States
CityPortland
Period2/25/173/1/17

Keywords

  • Creativity
  • Crowdsourcing
  • Data mining
  • Data visualization
  • Ideation
  • Microtasks

ASJC Scopus subject areas

  • Computer Networks and Communications

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  • Cite this

    Girotto, V., Walker, E., & Burleson, W. (2017). Scalable crowd ideation support through data visualization, mining, and structured workflows. In CSCW 2017 - Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 183-186). Association for Computing Machinery, Inc. https://doi.org/10.1145/3022198.3026349