Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/13342
Title: Accounting for diversity in subjective judgments
Authors: Karapanos, Evangelos 
Martens, Jean Bernard O.S. 
Hassenzahl, Marc 
Keywords: Multi-dimensional scaling;Quantitative methods;Repertory grid;Subjective judgments;User experience
Category: Computer and Information Sciences
Field: Natural Sciences
Issue Date: Apr-2009
Publisher: ACM
Source: 7th International Conference on Human Factors in Computing Systems, 2009, 4-9 April, Boston, MA, United States
Conference: 7th 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.
URI: http://ktisis.cut.ac.cy/handle/10488/13342
DOI: 10.1145/1518701.1518801
Rights: Copyright 2009 ACM.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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