Variation in the expression and annotation of emotions : a Wizard of Oz pilot study

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Labat, S., Ackaert, N., Demeester, T., & Hoste, V.
Gavin Abercrombie, Valerio Basile, Sara Tonelli, Verena Rieser and Alexandra Uma
Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022
European Language Resources Association (ELRA) (Marseille, France)
LREC 2022 Workshop : 1st Workshop on Perspectivist Approaches to NLP (NLPerspectives) (Marseille, France)
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This pilot study employs the Wizard of Oz technique to collect a corpus of written human-computer conversations in the domain of customer service. The resulting dataset contains 192 conversations and is used to test three hypotheses related to the expression and annotation of emotions. First, we hypothesize that there is a discrepancy between the emotion annotations of the participant (the experiencer) and the annotations of our external annotator (the observer). Furthermore, we hypothesize that the personality of the participants has an influence on the emotions they expressed, and on the way they evaluated (annotated) these emotions. We found that for an external, trained annotator, not all emotion labels were equally easy to work with. We also noticed that the trained annotator had a tendency to opt for emotion labels that were more centered in the valence-arousal space, while participants made more `extreme' annotations. For the second hypothesis, we discovered a positive correlation between the personality trait extraversion and the emotion dimensions valence and dominance in our sample. Finally, for the third premise, we observed a positive correlation between the internal-external agreement on emotion labels and the personality traits conscientiousness and extraversion. Our insights and findings will be used in future research to conduct a larger Wizard of Oz experiment.