research-article

CrowdMuse: Supporting Crowd Idea Generation through User Modeling and Adaptation

Authors:

Victor Girotto,

Winslow BurlesonAuthors Info & Claims

C&C '19: Proceedings of the 2019 Conference on Creativity and Cognition

Pages 95 - 106

https://doi.org/10.1145/3325480.3325497

Published: 13 June 2019 Publication History

Abstract

Online crowds, with their large numbers and diversity, show great potential for creativity. Research has explored different ways of augmenting their creative performance, particularly during large-scale brainstorming sessions. Traditionally, this comes in the form of showing ideators some form of inspiration to get them to explore more categories or generate more and better ideas. The mechanisms used to select which inspirations are shown to ideators thus far have not taken into consideration ideators' individualities, which could hinder the effectiveness of support. In this paper, we introduce and evaluate CrowdMuse, a novel adaptive system for supporting large-scale brainstorming. The system models ideators based on their past ideas and adapts the system views and inspiration mechanism accordingly. We evaluate CrowdMuse over two iterative large online studies and discuss the implication of our findings for designing adaptive creativity support systems.

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Cited By

Schleith JNorkute MMikhail MTsar DMaiden NSas C(2022)Cognitive Strategy PromptsProceedings of the 14th Conference on Creativity and Cognition10.1145/3527927.3532808(29-37)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1145/3527927.3532808
Bae SKwon OChandrasegaran SMa KBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Spinneret: Aiding Creative Ideation through Non-Obvious Concept AssociationsProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376746(1-13)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376746
Abbas TKhan VMarkopoulos P(2020)Investigating the Crowd’s Creativity for Creating On-Demand IoT ScenariosInternational Journal of Human–Computer Interaction10.1080/10447318.2019.170933136:11(1022-1049)Online publication date: 16-Jan-2020
https://doi.org/10.1080/10447318.2019.1709331
Show More Cited By

Index Terms

CrowdMuse: Supporting Crowd Idea Generation through User Modeling and Adaptation
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools

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Published In

C&C '19: Proceedings of the 2019 Conference on Creativity and Cognition

June 2019

745 pages

ISBN:9781450359177

DOI:10.1145/3325480

General Chairs:
Steven Dow
UC San Diego, USA
,
Mary Lou Maher
UNC Charlotte, USA
,
Program Chairs:
Andruid Kerne
Texas A&M University
,
Celine Latulipe
UNC Charlotte, USA

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 13 June 2019

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C&C '19: Creativity and Cognition

June 23 - 26, 2019

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C&C '19 Paper Acceptance Rate 30 of 101 submissions, 30%;

Overall Acceptance Rate 108 of 371 submissions, 29%

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Cited By

Schleith JNorkute MMikhail MTsar DMaiden NSas C(2022)Cognitive Strategy PromptsProceedings of the 14th Conference on Creativity and Cognition10.1145/3527927.3532808(29-37)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1145/3527927.3532808
Bae SKwon OChandrasegaran SMa KBernhaupt RMueller FVerweij DAndres JMcGrenere JCockburn AAvellino IGoguey ABjørn PZhao SSamson BKocielnik R(2020)Spinneret: Aiding Creative Ideation through Non-Obvious Concept AssociationsProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376746(1-13)Online publication date: 21-Apr-2020
https://dl.acm.org/doi/10.1145/3313831.3376746
Abbas TKhan VMarkopoulos P(2020)Investigating the Crowd’s Creativity for Creating On-Demand IoT ScenariosInternational Journal of Human–Computer Interaction10.1080/10447318.2019.170933136:11(1022-1049)Online publication date: 16-Jan-2020
https://doi.org/10.1080/10447318.2019.1709331
Chung JSong JKutty SHong SKim JLasecki W(2019)Efficient Elicitation Approaches to Estimate Collective Crowd AnswersProceedings of the ACM on Human-Computer Interaction10.1145/33591643:CSCW(1-25)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359164

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