AFEC: A knowledge graph capturing social intelligence in casual conversations

This paper presents AFEC, an automatically curated knowledge graph derived from everyday casual conversations. The graph’s encoded knowledge enhances conversational systems by modeling how people express acknowledgment, consolation, and empathy in social interactions. To construct a comprehensive and meaningful dataset, we curated a large-scale corpus from the r/CasualConversation subreddit. By extracting the first two turns of all conversations, we obtained 134K speaker nodes and 666K listener nodes. To illustrate the utility of AFEC, we developed a retrieval-based chatbot and compared its performance with existing empathetic dialogue models. Experimental results demonstrate that our chatbot generates significantly more diverse responses (achieving at least 15% higher diversity scores in human evaluations) while outperforming two of the four baseline models in terms of response quality. The data and code are publicly available at https://github.com/yuboxie/afec .