English

Turn-Level Empathy Prediction Using Psychological Indicators

Computation and Language 2024-07-12 v1

Abstract

For the WASSA 2024 Empathy and Personality Prediction Shared Task, we propose a novel turn-level empathy detection method that decomposes empathy into six psychological indicators: Emotional Language, Perspective-Taking, Sympathy and Compassion, Extroversion, Openness, and Agreeableness. A pipeline of text enrichment using a Large Language Model (LLM) followed by DeBERTA fine-tuning demonstrates a significant improvement in the Pearson Correlation Coefficient and F1 scores for empathy detection, highlighting the effectiveness of our approach. Our system officially ranked 7th at the CONV-turn track.

Keywords

Cite

@article{arxiv.2407.08607,
  title  = {Turn-Level Empathy Prediction Using Psychological Indicators},
  author = {Shaz Furniturewala and Kokil Jaidka},
  journal= {arXiv preprint arXiv:2407.08607},
  year   = {2024}
}
R2 v1 2026-06-28T17:37:33.154Z