Sociophysics Theory for Conflict of Viewer Rating on Television Program

Ishii, Akira; Nishiyama, Daiki; Suzuki, Yasuyuki

doi:10.1007/978-3-030-37442-6_24

Sociophysics Theory for Conflict of Viewer Rating on Television Program

Proposal of New Index Instead of Viewer Rating

Akira Ishii⁶,
Daiki Nishiyama⁶ &
Yasuyuki Suzuki⁷

Conference paper
First Online: 05 December 2019

314 Accesses

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 12))

Abstract

The competing viewers from multiple TV stations is a fierce competition. This competition is contested in the form of viewer rating of how much is viewed. In this study, the viewer’s viewing behavior is formulated in the form of transport equation. Audiences gather in interesting scenes, and viewers leave from boring scenes. We propose a theory to quantify the fun of the program based on these viewing behaviors. The degree of interest from moment to moment according to this theory does not match the audience rating.

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References

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Acknowledgements

We are grateful for Dr. Yasuko Kawahata for fruitful discussions.

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Authors and Affiliations

Department of Applied Mathematics and Physics, Tottori University Koyama, Tottori, 680-8552, Japan
Akira Ishii & Daiki Nishiyama
Video Research Ltd. 6-17, Sanban-cho, Chiyoda-ku, Tokyo, 102-0075, Japan
Yasuyuki Suzuki

Authors

Akira Ishii
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Daiki Nishiyama
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Yasuyuki Suzuki
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Corresponding author

Correspondence to Akira Ishii .

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Editors and Affiliations

Department of Computer Science, National Defense Academy of Japan, Yokosuka-shi, Japan
Hiroshi Sato
Faculty of Maritime Safety Technology, Japan Coast Guard Academy, Wakabacho, Japan
Saori Iwanaga
Department of Applied Mathematics and Physics, Tottori University, Tottori, Japan
Akira Ishii

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Ishii, A., Nishiyama, D., Suzuki, Y. (2020). Sociophysics Theory for Conflict of Viewer Rating on Television Program. In: Sato, H., Iwanaga, S., Ishii, A. (eds) Proceedings of the 23rd Asia Pacific Symposium on Intelligent and Evolutionary Systems. IES 2019. Proceedings in Adaptation, Learning and Optimization, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-37442-6_24

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DOI: https://doi.org/10.1007/978-3-030-37442-6_24
Published: 05 December 2019
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37441-9
Online ISBN: 978-3-030-37442-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)

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