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Emotion-based character clustering for managing story-based contents: a cinemetric analysis

Published: 01 July 2013 Publication History

Abstract

Stories in digital content (e.g., movies) are usually developed using many kinds of relationships among the characters. In order to efficiently manage such contents, we want to exploit a social network (called Character-net) extracted from the stories. Since scripts are composed of several elements (i.e., scene headings, character names, dialogs, actions, etc.), we focus on analyzing interactions (e.g., dialog) among the characters to build such a social network. Most importantly, these relationships between minor and major characters can be abstracted and clustered into similar scenes. Thereby, in this paper, we propose a novel method that can cluster characters using their emotional similarity. If a minor character has a similar emotion vector tothe main character, then the minor character can be classified as a tritagonist who helps the main character. Conversely, this minor character may be clustered into another group and denoted as an antagonist. Additionally, we show the efficiency of our proposed method by experiment in this paper.

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  • (2020)Using weighted directed graphs for identification of flow of emotions in poemsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-17988539:2(2213-2227)Online publication date: 1-Jan-2020
  • (2020)Towards Story-based Summarization of Narrative MultimediaProceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications10.1145/3440943.3444719(1-5)Online publication date: 12-Dec-2020
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Published In

cover image Multimedia Tools and Applications
Multimedia Tools and Applications  Volume 65, Issue 1
July 2013
175 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2013

Author Tags

  1. Character clustering
  2. Character-net
  3. Emotion
  4. Relationship
  5. Social network

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  • (2021)Detection of the helper types from story in multimediaMultimedia Tools and Applications10.1007/s11042-020-08778-w80:26-27(34479-34497)Online publication date: 1-Nov-2021
  • (2020)Using weighted directed graphs for identification of flow of emotions in poemsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-17988539:2(2213-2227)Online publication date: 1-Jan-2020
  • (2020)Towards Story-based Summarization of Narrative MultimediaProceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications10.1145/3440943.3444719(1-5)Online publication date: 12-Dec-2020
  • (2019)Extraction and Analysis of Fictional Character NetworksACM Computing Surveys10.1145/334454852:5(1-40)Online publication date: 13-Sep-2019
  • (2019)Modeling affective character network for story analyticsFuture Generation Computer Systems10.1016/j.future.2018.01.03092:C(458-478)Online publication date: 1-Mar-2019
  • (2017)Character-based indexing and browsing with movie ontology Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16912232:2(1229-1240)Online publication date: 1-Jan-2017
  • (2017)Exploiting character networks for movie summarizationMultimedia Tools and Applications10.1007/s11042-016-3633-676:8(10357-10369)Online publication date: 1-Apr-2017
  • (2017)A computational model of transmedia ecosystem for story-based contentsMultimedia Tools and Applications10.1007/s11042-016-3626-576:8(10371-10388)Online publication date: 1-Apr-2017
  • (2013)Comparative study of text clustering techniques in virtual worldsProceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics10.1145/2479787.2479818(1-8)Online publication date: 12-Jun-2013

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