Comic character relationships are an essential aspect of understanding comic content. These relationships are often expressed in a character correlation diagram. However, existing diagrams with complex relationships can confuse users, and simple correlation diagrams do not show information on character personalities. Therefore, it is necessary to 1) make these diagrams more visually clear and 2) to display character personality information in addition to relationships without increasing the diagram complexity. This paper presents an interactive visualization system for character correlation diagrams that display complex character relationships and personalities. We propose a relationship labeling method based on FOAF and implement a user selection function to emphasize specified relationships visually. This paper also provides visualizations of character personalities chosen by the user. Consequently, users can understand both comic character personalities and relationships. This paper verified whether users could correctly find a specific relationship when asked.
Proc. the 24th International Conference on Information Integration and Web Intelligence
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Date of presentation
Kanna Miyagawa, Yutaka Morino, Mitsunori Matsushita. Interactive visualization of comic character correlation diagrams for understanding character relationships and personalities, Proc. the 24th International Conference on Information Integration and Web Intelligence, pp.561-567, 2022.