Research on Cultural Film and Television Criticism and User Behavior Communication Model Based on Sentiment Analysis

Yiran Li ()
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Yiran Li: Xinyang Agriculture and Forestry University, School of Humanities and Communication

A chapter in Proceedings of 2024 4th International Conference on Public Management and Big Data Analysis (PMBDA 2024), 2025, pp 209-219 from Springer

Abstract: Abstract To enhance the interpretative efficiency of cultural film and television reviews and the accuracy of user behavior prediction, sentiment analysis technology is applied to assess the polarity and intensity of film and television reviews. This approach aims to identify users’ emotional attitudes toward films and predict their interactive behaviors. By collecting 2,000 data entries from social media and film review platforms, a deep learning model based on Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks achieved an overall accuracy rate of 88% in sentiment classification. Additionally, experimental results indicate that reviews with high emotional intensity significantly increase the probability of dissemination behaviors such as likes and shares, highlighting the critical role of emotional information in driving user behavior.

Keywords: sentiment analysis; film reviews; user behavior prediction (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-656-7_21

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DOI: 10.2991/978-94-6463-656-7_21

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