Communication Dans Un Congrès Année : 2020

Movies Emotional Analysis Using Textual Contents

Résumé

In this paper, we use movies and series subtitles and applied text mining and Natural Language Processing methods to evaluate emotions in videos. Three different word lexicons were used and one of the outcomes of this research is the generation of a secondary dataset with more than 3658 records which can be used for other data analysis and data mining research. We used our secondary dataset to find and display correlations between different emotions on the videos and the correlation between emotions on the movies and users' scores on IMDb using the Pearson correlation method and found some statistically significant correlations.

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Dates et versions

hal-02561371 , version 1 (03-05-2020)

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  • HAL Id : hal-02561371 , version 1

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Amir Kazem Kayhani, Farid Meziane, Raja Chiky. Movies Emotional Analysis Using Textual Contents. NLDB, Jun 2020, Saarbrücken, Germany. ⟨hal-02561371⟩

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