Decipher: An Interactive Visualization Tool for Interpreting Unstructured Design Feedback from Multiple Providers

Yu Chun Grace Yen, Joy O. Kim, Brian P. Bailey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

Abstract

Feedback from diverse audiences can vary in focus, differ in structure, and contradict each other, making it hard to interpret and act on. While prior work has explored generating quality feedback, our work helps a designer interpret that feedback. Through a formative study with professional designers (N=10), we discovered that the interpretation process includes categorizing feedback, identifying valuable feedback, and prioritizing which feedback to incorporate in a revision. We also found that designers leverage feedback topic and sentiment, and the status of the provider to aid interpretation. Based on the findings, we created a new tool (Decipher) that enables designers to visualize and navigate a collection of feedback using its topic and sentiment structure. In a preliminary evaluation (N=20), we found that Decipher helped users feel less overwhelmed during feedback interpretation tasks and better attend to critical issues and conflicting opinions compared to using a typical document-editing tool.

Original languageEnglish
Title of host publicationCHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450367080
DOIs
StatePublished - 21 Apr 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States
Duration: 25 Apr 202030 Apr 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
Country/TerritoryUnited States
CityHonolulu
Period25/04/2030/04/20

Keywords

  • creativity
  • creativity support tools
  • feedback
  • sense-making

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