Hye-Yeon Yu, Moon-Hyun Kim, Byung-Chull Bae, Journal of Internet Computing and Services, Vol. 22, No. 1, pp. 51-63, Feb. 2021
10.7472/jksii.2021.22.1.51, Full Text:  HTML
Keywords: Actantial model, Character Role Recognition, Character Relationship Graph, Character Sentiment Flow Graph

Abstract

Identifying characters who appear in a story and analyzing their relationships is essential to understanding the story. This paper aims to identify the two actants (or character roles) as Helper and Opponent in Greimas's Actantial model by identifying Subject (i.e., protagonist) and analyzing the emotional interactions between the Subject and the two actants (Helper/Opponent). Our proposed method consists of three steps. First, we identify objects (i.e., characters) appearing in the text story. Next, we extract relational information through the interaction of the characters, and then classify emotions in the text expressed as relational information. Finally, we represent the flow of emotional relations among characters as a directed graph. The node with the highest degree is considered as the Subject because it includes the most relational information. The node that sends the most positive/negative emotions to the Subject is considered as the Helper/Oppenent, respectively. Our research contributes to the computer-based narrative understanding by providing a computational method that automatically extracts the three key character roles (Subject, Helper, and Opponent) from the text story.

Statistics
Cite this article