Turn-Level Empathy Prediction Using Psychological Indicators

Shaz Furniturewala; Kokil Jaidka

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arXiv · 2407.08607

Turn-Level Empathy Prediction Using Psychological Indicators

Shaz Furniturewala·Kokil Jaidka

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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.

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Shaz Furniturewala, Kokil Jaidka. 2024-07-11. Turn-Level Empathy Prediction Using Psychological Indicators. https://arxiv.org/abs/2407.08607

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