Abstract
This research contributes to the task of predicting empathy and personality traits within dialogue, an important aspect of natural language processing, as part of our experimental work for the WASSA 2023 Empathy and Emotion Shared Task. For predicting empathy, emotion polarity, and emotion intensity on turns within a dialogue, we employ adapters trained on social media interactions labeled with empathy ratings in a stacked composition with the target task adapters. Furthermore, we embed demographic information to predict Interpersonal Reactivity Index (IRI) subscales and Big Five Personality Traits utilizing BERT-based models. The results from our study provide valuable insights, contributing to advancements in understanding human behavior and interaction through text. Our team ranked 2nd on the personality and empathy prediction tasks, 4th on the interpersonal reactivity index, and 6th on the conversational task.- Anthology ID:
- 2023.wassa-1.50
- Volume:
- Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Jeremy Barnes, Orphée De Clercq, Roman Klinger
- Venue:
- WASSA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 553–557
- Language:
- URL:
- https://aclanthology.org/2023.wassa-1.50
- DOI:
- 10.18653/v1/2023.wassa-1.50
- Cite (ACL):
- Fabio Gruschka, Allison Lahnala, Charles Welch, and Lucie Flek. 2023. Domain Transfer for Empathy, Distress, and Personality Prediction. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 553–557, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Domain Transfer for Empathy, Distress, and Personality Prediction (Gruschka et al., WASSA 2023)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.wassa-1.50.pdf