Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/13342
Title: | Accounting for diversity in subjective judgments | Authors: | Karapanos, Evangelos Martens, Jean Bernard O.S. Hassenzahl, Marc |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Keywords: | Multi-dimensional scaling;Quantitative methods;Repertory grid;Subjective judgments;User experience | Issue Date: | Apr-2009 | Source: | 7th International Conference on Human Factors in Computing Systems, 2009, 4-9 April, Boston, MA, United States | Conference: | International Conference on Human Factors in Computing Systems | Abstract: | In this paper we argue against averaging as a common practice in the analysis of subjective attribute judgments, both across and within subjects. Previous work has raised awareness of the diversity between individuals' perceptions. In this paper it will furthermore become apparent that such diversity can also exist within a single individual, in the sense that different attribute judgments from a subject may reveal different, complementary, views. A Multi- Dimensional Scaling approach that accounts for the diverse views on a set of stimuli is proposed and its added value is illustrated using published data. We will illustrate that the averaging analysis provides insight to only l/6th of the total number of attributes in the example dataset. The proposed approach accounts for more than double the information obtained from the average model, and provides richer and semantically diverse views on the set of stimuli. | DOI: | 10.1145/1518701.1518801 | Rights: | Copyright ACM | Type: | Conference Papers | Affiliation : | Eindhoven University of Technology Folkwang University of the Arts |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
SCOPUSTM
Citations
20
checked on Nov 6, 2023
Page view(s)
341
Last Week
0
0
Last month
2
2
checked on Nov 21, 2024
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.