Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality

Jiashuo Wang, Wenjie Li, Peiqin Lin, Feiteng Mu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)


Empathetic response generation aims to comprehend the user emotion and then respond to it appropriately. Most existing works merely focus on what the emotion is and ignore how the emotion is evoked, thus weakening the capacity of the model to understand the emotional experience of the user for generating empathetic responses. To tackle this problem, we consider the emotional causality, namely, what feelings the user expresses (i.e., emotion) and why the user has such feelings (i.e., cause). Then, we propose a novel graph-based model with multi-hop reasoning to model the emotional causality of the empathetic conversation. Finally, we demonstrate the effectiveness of our model on EMPATHETICDIALOGUES in comparison with several competitive models.

Original languageEnglish
Article number107547
Pages (from-to)1-10
JournalKnowledge-Based Systems
Publication statusPublished - 5 Dec 2021


  • Commonsense knowledge graph
  • Empathetic response generation
  • Multi-hop reasoning

ASJC Scopus subject areas

  • Management Information Systems
  • Software
  • Information Systems and Management
  • Artificial Intelligence


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