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The ordinal nature of emotions
- Source :
- ACII
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- Representing computationally everyday emotional states is a challenging task and, arguably, one of the most fundamental for affective computing. Standard practice in emotion annotation is to ask humans to assign an absolute value of intensity to each emotional behavior they observe. Psychological theories and evidence from multiple disciplines including neuroscience, economics and artificial intelligence, however, suggest that the task of assigning reference-based (relative) values to subjective notions is better aligned with the underlying representations than assigning absolute values. Evidence also shows that we use reference points, or else anchors, against which we evaluate values such as the emotional state of a stimulus; suggesting again that ordinal labels are a more suitable way to represent emotions. This paper draws together the theoretical reasons to favor relative over absolute labels for representing and annotating emotion, reviewing the literature across several disciplines. We go on to discuss good and bad practices of treating ordinal and other forms of annotation data, and make the case for preference learning methods as the appropriate approach for treating ordinal labels. We finally discuss the advantages of relative annotation with respect to both reliability and validity through a number of case studies in affective computing, and address common objections to the use of ordinal data. Overall, the thesis that emotions are by nature relative is supported by both theoretical arguments and evidence, and opens new horizons for the way emotions are viewed, represented and analyzed computationally.<br />peer-reviewed
- Subjects :
- Cognitive science
Ordinal data
New horizons
Preference learning
02 engineering and technology
Human-computer interaction
Data modeling
030507 speech-language pathology & audiology
03 medical and health sciences
Annotation
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0202 electrical engineering, electronic engineering, information engineering
Task analysis
020201 artificial intelligence & image processing
Emotion recognition
0305 other medical science
Psychology
Affective computing
Cognitive psychology
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)
- Accession number :
- edsair.doi.dedup.....60913667366c5326faa543e207670be5