中国邮电高校学报(英文) ›› 2022, Vol. 29 ›› Issue (5): 73-82.doi: 10.19682/j.cnki.1005-8885.2022.0006

• Artificial Intelligence • 上一篇    下一篇

Research on emotional space for movie and TV drama videos

李玉杰,张晶晶,蒋伟,王春晓   

  1. 中国传媒大学
  • 收稿日期:2021-05-31 修回日期:2021-09-16 出版日期:2022-10-31 发布日期:2022-10-28
  • 通讯作者: 张晶晶 E-mail:zjj_cuc@cuc.edu.cn
  • 基金资助:
    文旅部重点实验室基金

Research on emotional space for movie and TV drama videos

Li Yujie1,2,3, Zhang Jingjing1,2,4, Jiang Wei1,2, Wang Chunxiao1,2,3   

  • Received:2021-05-31 Revised:2021-09-16 Online:2022-10-31 Published:2022-10-28
  • Supported by:
    the Key Laboratory Foundation of the Ministry of Culture and Tourism

摘要:

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding (t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.


关键词: emotional space| movie and TV drama videos| subjective evaluation| words semantic analysis| fusion space

Abstract:

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding (t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.


Key words: emotional space| movie and TV drama videos| subjective evaluation| words semantic analysis| fusion space

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