Abstract
Our system, IUCL, participated in the WASSA 2022 Shared Task on Empathy Detection and Emotion Classification. Our main goal in building this system is to investigate how the use of demographic attributes influences performance. Our results show that our text-only systems perform very competitively, ranking first in the empathy detection task, reaching an average Pearson correlation of 0.54, and second in the emotion classification task, reaching a Macro-F of 0.572. Our systems that use both text and demographic data are less competitive.
Cite
CITATION STYLE
Chen, Y., Ju, Y., & Kübler, S. (2022). IUCL at WASSA 2022 Shared Task: A Text-Only Approach to Empathy and Emotion Detection. In WASSA 2022 - 12th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop (pp. 228–232). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.wassa-1.21
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