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Analyzing Textual Sources Attributes of Comics Based on Word Frequency and Meaning

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Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges (ICPR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13644))

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Abstract

The purpose of this research is to analyze the textual source attributes of explanations and reviews about comics. Comics are difficult to process in terms of the intended story because they are primarily composed of pictures and text. One of the processing methods is to analyze comics text on the Web, particularly the description of characters and reviews including the reader’s impression about the comic. Sources of textual information, such as explanations or reviews, are selected according to the application of the study. However, differences among textual sources regarding comics are not taken into consideration in the analysis. This paper classifies words appearing frequently in the text semantically, with results showing that explanations include words that express the story, for example, the family structure, physical information, and sex of the characters for describing the characters. Conversely, the review frequently uses words that provide meta-information about comics, such as illustrations and style. The proposed method revealed that explanations of comics are more useful as textual sources for analyzing story information than reviews.

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Notes

  1. 1.

    https://sp.comics.mecha.cc, (confirmed September 2nd, 2022).

  2. 2.

    https://ja.wikipedia.org/wiki/ (confirmed September 2nd, 2022).

  3. 3.

    https://dic.nicovideo.jp (confirmed September 2nd, 2022).

  4. 4.

    https://dic.pixiv.net (confirmed September 2nd, 2022).

  5. 5.

    https://w.atwiki.jp/aniwotawiki/ (confirmed September 2nd, 2022).

  6. 6.

    https://sakuhindb.com/ (confirmed September 2nd, 2022).

  7. 7.

    http://www.hottolink.co.jp/english/ (confirmed September 2nd, 2022).

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Acknowledgement

This work is supported by JSPS KAKENHI Grant Number #22K12338.

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Authors and Affiliations

  1. Kansai University, 2-1-1 Ryozenijicho, Takatsukishi, Osaka, 569-1095, Japan

    Ryota Higuchi, Ryosuke Yamanishi & Mitsunori Matsushita

Authors
  1. Ryota Higuchi
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  2. Ryosuke Yamanishi
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  3. Mitsunori Matsushita
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Corresponding author

Correspondence to Ryota Higuchi .

Editor information

Editors and Affiliations

  1. York University, Toronto, ON, Canada

    Jean-Jacques Rousseau

  2. Ontario Tech University, Oshawa, ON, Canada

    Bill Kapralos

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Higuchi, R., Yamanishi, R., Matsushita, M. (2023). Analyzing Textual Sources Attributes of Comics Based on Word Frequency and Meaning. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13644. Springer, Cham. https://doi.org/10.1007/978-3-031-37742-6_8

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  • DOI: https://doi.org/10.1007/978-3-031-37742-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37741-9

  • Online ISBN: 978-3-031-37742-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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