Work

Classifying Personalities of Comic Characters Based on Egograms

Year: 2018

Type: conference-paper

Abstract: The aim of this research is to develop a search system for comics based on the personalities of appearing characters. For this purpose, this paper describes the classification of characters using egograms, which are used to classify personalities. In the proposed method, texts that express a comic book character's personality are acquired from web resources, and semantic vectors are allocated based on these texts using egograms. The resulting egogram pattern is used to estimate typical properties. Our experiment reveals that the performance accuracy of this classification method is 55.0%.

Source: International Symposium on Affective Science and Engineering

DOI: 10.5057/isase.2018-c000029

Authors: Byeongseon PARK, Kanae IBAYASHI, Mitsunori MATSUSHITA

Institution: Kansai University

Language: English

Topic: Comics and Graphic Narratives

Subfield: Visual Arts and Performing Arts

Field: Arts and Humanities

Domain: Social Sciences

Open Access status: diamond

Funder: Japan Society for the Promotion of Science

Award: Information Compilation Technologies for Comic Contents