A Computational Model to Detect Affective Response Based on Narrative Agent’s Knowledge

Abstract

Narratives arouse diverse and rich affective responses to recipients, and this is one of the reasons why narratives are universal and popular. Computational studies on narratives have established a formal model or system of the affective response based on the theory in psychology or media research, and have analyzed or generated a narrative that can evoke a specific affective response. In this paper, we propose a new computational model that can detect the affective response expected to appear in the narrative based on the narrative agent’s knowledge. First, we designed a narrative representation model that can elaborately express the event structure and the agent’s knowledge as well. Additionally, an analysis method was proposed to detect the three affective responses and the related situational information. Then, we validated the model through a case study about an actual movie narrative. Through the case study, we confirmed that the model captures the affective responses of the audience. The proposed model can be effectively used for the narrative analysis and the creation that must consider the affective responses of the recipient.