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A Discussion of the Application of Artificial Intelligence In the Management of Mass Media Censorship in Mainland China

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Published:20 August 2020Publication History

ABSTRACT

Today, artificial intelligence (AI) has rapidly entered our daily life, such as face recognition technology has been used in all walks of life. In the new era, the management of mass media censorship system in Mainland China is changing through artificial intelligence. The media industry has become more convenient and effective from editing to censorship by using artificial intelligence technology. In the future, the researcher thinks facial recognition could even be used to aid the implementation of "Motion Picture Content Rating System" in Mainland China. Therefore, artificial intelligence will continue to promote the progress of the censorship system of mass media in Mainland China and become the driving force for the booming development of mass media in Mainland China under the new era. This paper will summarize the history of the censorship system of mass media and analyzes the development of the censorship system management of mass media in Mainland China, as well as discuss the using of artificial intelligence and the possibility of its future use.

References

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  2. Xu, B. N. (2015). "Media Censorship in China". Council on Foreign Relations.Google ScholarGoogle Scholar
  3. Ng, Y. (2002). "The Irresistible Rise of Asian Cinema-Tian Zhuangzhuang: A Director of the 21st Century".Google ScholarGoogle Scholar
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  5. Mei, F. & Li, E.S., & Zhong, D.F. (2016). Film Censorship: Things You've Always Wanted to Know but Never Asked. Ginkgo (Beijing) Book Co., Ltd. ISBN 978-7-5502-8245-2.Google ScholarGoogle Scholar

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  1. A Discussion of the Application of Artificial Intelligence In the Management of Mass Media Censorship in Mainland China

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      cover image ACM Other conferences
      AICSconf '20: Proceedings of the 2020 Artificial Intelligence and Complex Systems Conference
      August 2020
      166 pages
      ISBN:9781450377270
      DOI:10.1145/3407703

      Copyright © 2020 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 August 2020

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      • research-article
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      • Refereed limited

      Acceptance Rates

      AICSconf '20 Paper Acceptance Rate28of153submissions,18%Overall Acceptance Rate28of153submissions,18%

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