skip to main content
10.1145/2901790.2901791acmconferencesArticle/Chapter ViewAbstractPublication PagesdisConference Proceedingsconference-collections
research-article

A Picture Paints a Thousand Words but Can it Paint Just One?

Published:04 June 2016Publication History

ABSTRACT

Imagery and language are often seen as serving different aspects of cognition, with cognitive styles theories proposing that people can be visual or verbal thinkers. Most feedback systems, however, only cater to verbal thinkers. To help rectify this, we have developed a novel method of crowd communication which appeals to those more visual people. Designers can ask a crowd to feedback on their designs using specially constructed image banks to discover the perceptual and emotional theme perceived by possible future customers. A major component of the method is a summarization process in which the crowd's feedback, consisting of a mass of images, is presented to the designer as a digest of representative images. In this paper we describe an experiment showing that these image summaries are as effective as the full image selections at communicating terms. This means that designers can consume the new feedback confident that it represents a fair representation of the total image feedback from the crowd.

Skip Supplemental Material Section

Supplemental Material

pn102.mp4

mp4

39 MB

References

  1. Chris Andrzejczak & Dahai Liu. (2010). The effect of testing location on usability testing performance, participant stress levels, and subjective testing experience. Journal of Systems and Software, 83(7), 1258--1266 Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Colin F. Camerer, & Robin M. Hogarth. (1999). The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework. Journal of Risk and Uncertainty, 19(1--3), 7--42Google ScholarGoogle ScholarCross RefCross Ref
  3. Daniel Chandler. 2002. Semiotics : the basics (2nd ed.), Routledge.Google ScholarGoogle Scholar
  4. Alasdair D.F. Clarke, Fraser Halley, Andrew J. Newell, Lewis D. Griffin, & Mike J. Chantler. 2011. Perceptual similarity: a texture challenge. In Proceedings of the 22nd British Machine Vision Conference (BMVC'11), 120.Google ScholarGoogle ScholarCross RefCross Ref
  5. Trevor F. Cox, & Michael A. A. Cox. 2001. Multidimensional Scaling (Second Edition ed.). Chapman & Hall/CRC.Google ScholarGoogle ScholarCross RefCross Ref
  6. Jonathan Culler. 1976. Saussure. Fontana.Google ScholarGoogle Scholar
  7. Elise S. Dan-Glauser & Klaus R. Scherer. 2011. The 8 Geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance. Behavior Research Methods, 43(2), 468--477.Google ScholarGoogle ScholarCross RefCross Ref
  8. Dribbble 2015. https://dribbble.com/ (Last accessed January 10/2015)Google ScholarGoogle Scholar
  9. Claudia Eckert & Martin Stacey. 2000. Sources of inspiration: a language of design. Design Studies, 21(5), 523--538.Google ScholarGoogle ScholarCross RefCross Ref
  10. Brian Everitt 1974. Cluster Analysis. Heinemann.Google ScholarGoogle Scholar
  11. Andy Field 2009. Discovering Statistics Using SPSS (3rd ed.) Sage.Google ScholarGoogle Scholar
  12. Steve Garner & Deana McDonagh-Philp. 2001. Problem interpretation and resolution via visual stimuli: the use of "mood boards" in design education. Journal of Art & Design Education, 20(1), 57--64.Google ScholarGoogle ScholarCross RefCross Ref
  13. Pierre Guiraud. 1971. Semiology, Routledge.Google ScholarGoogle Scholar
  14. Joeri Hofmans and Peter Theuns. 2008. On the linearity of predefined and self-anchoring Visual Analogue Scales. British Journal of Mathematical and Statistical Psychology, 61(Pt 2).Google ScholarGoogle Scholar
  15. Roman Jakobson. 1960. Closing statement: Linguistics and poetics. Style in language, 350, 377.Google ScholarGoogle Scholar
  16. Teuvo Kohonen. 1990. The self-organizing map. Proceedings of the Institute of Electrical and Electronics Engineers, 78(9), 1464--1480.Google ScholarGoogle ScholarCross RefCross Ref
  17. Gunther R Kress, & Theo Van Leeuwen. 1996. Reading images: The grammar of visual design, Psychology Press.Google ScholarGoogle Scholar
  18. Joseph B. Kruskal 1964. Nonmetric multidimensional scaling: A numerical method. Psychometrika, 29(2), 115--129.Google ScholarGoogle ScholarCross RefCross Ref
  19. Peter J. Lang, Margaret M. Bradley, & Bruce N. Cuthbert. 2008. International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical Report A-8.University of Florida.Google ScholarGoogle Scholar
  20. Lerner, J.S., Small, D.A. and Loewenstein, G. 2004. Research Report Heart Strings and Purse Strings Carryover Effects of Emotions on Economic Decisions. Psychological Science, 15(5), APS, 337--341Google ScholarGoogle Scholar
  21. David McCandless. (2009). Information is beautiful. Collins.Google ScholarGoogle Scholar
  22. Albert Mehrabian & Susan R. Ferris. 1967. Inference of attitudes from nonverbal communication in two channels. Journal of consulting psychology, 31(3), 248.Google ScholarGoogle ScholarCross RefCross Ref
  23. Albert Mehrabian & Morton Wiener. 1967. Decoding of inconsistent communications. Journal of personality and social psychology, 6(1), 10.Google ScholarGoogle ScholarCross RefCross Ref
  24. Thomas S. Methven, Pawel M. Orzechowski, Mike J. Chantler, Sharon Baurley & Douglas Atkinson. 2011. Comparison of Crowd-Sourcing vs. Traditional Techniques for Deriving Consumer Terms. In Digital Engagement '11, http://de2011.computing.dundee.ac.uk/?page_id=211 (last accessed September 24th 2015).Google ScholarGoogle Scholar
  25. Mitsuo Nagamachi. 1995. Kansei engineering: a new ergonomic consumer-oriented technology for product development, International Journal of Industrial Ergonomics 15(1), 3--11.Google ScholarGoogle ScholarCross RefCross Ref
  26. Stefano Padilla, Fraser Halley, David A. Robb, and Mike J. Chantler. 2013. Intuitive Large Image Database Browsing using Perceptual Similarity Enriched by Crowds. In Proceedings of the 15th International Conference on Computer Analysis of Images and Patterns (CAIP'13), Springer, 169--176.Google ScholarGoogle Scholar
  27. Stefano Padilla, David A. Robb, Fraser Halley, & Mike J. Chantler. 2012. Browsing Abstract Art by Appearance. In Proceedings of the 3rd International Conference on Appearance: Predicting Perceptions, Lulu Press, 100--103.Google ScholarGoogle Scholar
  28. Sathish Pammi & Marc Schröder. 2009. Annotating meaning of listener vocalizations for speech synthesis. In Proceedings of 3rd IEEE International Conference on Affective Computing and Intelligent Interaction (ACII'09), 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  29. Mick J. Power. 2006. The structure of emotion: An empirical comparison of six models. Cognition & Emotion, 20(5), 694--713Google ScholarGoogle ScholarCross RefCross Ref
  30. Ulf-Dietrich Reips and Frederik Funke. 2008. Intervallevel measurement with visual analogue scales in Internet-based research: VAS Generator. Behavior Research Methods, 40(3), 699--704.Google ScholarGoogle ScholarCross RefCross Ref
  31. David A. Robb, Stefano Padilla, Britta Kalkreuter, and Mike J. Chantler. 2015. Moodsource: Enabling Perceptual and Emotional Feedback from Crowds. In Proceedings of the ACM Conference Companion on Computer Supported Cooperative Work & Social Computing (CSCW'15), 21--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. David A. Robb, Stefano Padilla, Britta Kalkreuter, and Mike J. Chantler. 2015. Crowdsourced Feedback With Imagery Rather Than Text: Would Designers Use It? In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI'15), 1355--1364. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Mark A. Runco. 2014. Creativity: Theories and themes: Research, development, and practice, Elsevier.Google ScholarGoogle Scholar
  34. Vera Sacharin, Katja Schlegel and K. R. Scherer. 2012. Geneva Emotion Wheel rating study (Report). University of Geneva, Swiss Center for Affective Sciences.Google ScholarGoogle Scholar
  35. Klaus R. Scherer. 2005. What are emotions? And how can they be measured? Social Science Information, 44(4), 695--729.Google ScholarGoogle ScholarCross RefCross Ref
  36. Norbert Schwarz, Herbert Bless, & Gerd Bohner. 1991. Mood and persuasion: Affective states influence the processing of persuasive communications. Advances in experimental social psychology, 24, 161--199.Google ScholarGoogle Scholar
  37. Ingo Siegert, Böck Bock, Bogdan Vlasenko, David Philippou-Hubner & Andreas Wendemuth. 2011. Appropriate emotional labelling of non-acted speech using basic emotions, Geneva emotion wheel and selfassessment manikins. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME'11), 1--6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Joan G Snodgrass, & Mary Vanderwart. 1980. A standardized set of 260 pictures: norms for name agreement, image agreement, familiarity, and visual complexity. Journal of experimental psychology: Human learning and memory, 6(2), 174.Google ScholarGoogle ScholarCross RefCross Ref
  39. Mohammad Soleymani & Maja Pantic 2012. Humancentered implicit tagging: Overview and perspectives. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC'12), 3304--3309.Google ScholarGoogle Scholar
  40. Andrew R H Swan & Michael Sandilands. 1995. Introduction to geological data analysis, Blackwell. 174--177.Google ScholarGoogle Scholar
  41. Larissa Z. Tiedens and Susan Linton. 2001. Judgment under emotional certainty and uncertainty: the effects of specific emotions on information processing. Journal of personality and social psychology, 81(6), APA, 973.Google ScholarGoogle ScholarCross RefCross Ref
  42. Tom Tullis, Stan Fleischman, Michelle McNulty, Carrie Cianchette & Margaret Bergel. 2002. An empirical comparison of lab and remote usability testing of web sites.Google ScholarGoogle Scholar
  43. Johan H. J. Vesanto, Esa Alhoniemi and Juha Parhankangas. 1999. Self-organizing map in Matlab: The SOM Toolbox. In Procedings of the Matlab DSP Conference. 35--40.Google ScholarGoogle Scholar

Index Terms

  1. A Picture Paints a Thousand Words but Can it Paint Just One?

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      DIS '16: Proceedings of the 2016 ACM Conference on Designing Interactive Systems
      June 2016
      1374 pages
      ISBN:9781450340311
      DOI:10.1145/2901790

      Copyright © 2016 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].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 4 June 2016

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      DIS '16 Paper Acceptance Rate107of418submissions,26%Overall Acceptance Rate1,158of4,684submissions,25%

      Upcoming Conference

      DIS '24
      Designing Interactive Systems Conference
      July 1 - 5, 2024
      IT University of Copenhagen , Denmark

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader