CrowdMuse: An adaptive crowd brainstorming system

Victor Girotto, Erin Walker, Winslow Burleson

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


Online crowds, with their large numbers and diversity, show great potential for creativity, particularly during large-scale brainstorming sessions. Research has explored different ways of augmenting this creativity, such as showing ideators some form of inspiration to get them to explore more categories or generate more ideas. The mechanisms used to select which inspirations are shown to ideators thus far have been focused on characteristics of the inspirations rather than on ideators. This can hinder their effect, as creativity research has shown that ideators have unique cognitive structures and may therefore be better inspired by some ideas rather than others. We introduce CrowdMuse, an adaptive system for supporting large scale brainstorming. The system models ideators based on their past ideas and adapts the system views and inspiration mechanisms accordingly. An evaluation of this system could inform how to better individually support ideators.

Original languageEnglish (US)
Title of host publicationUIST 2018 Adjunct - Adjunct Publication of the 31st Annual ACM Symposium on User Interface Software and Technology
PublisherAssociation for Computing Machinery, Inc
Number of pages3
ISBN (Electronic)9781450359498
StatePublished - Oct 11 2018
Event31st Annual ACM Symposium on User Interface Software and Technology, UIST 2018 - Berlin, Germany
Duration: Oct 14 2018Oct 17 2018


Other31st Annual ACM Symposium on User Interface Software and Technology, UIST 2018


  • Adaptive systems
  • Brainstorming
  • Creativity
  • Crowd

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software


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