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Machine Learning Based Sentiment Analysis of Movie Reviews——A case study of “Beyond the Clouds”

Published: 29 May 2024 Publication History

Abstract

With the rapid development of Internet technology, major movie information platforms contain a huge amount of online review text data, mining and analyzing the viewpoints of the reviews as well as the hidden emotions have important commercial value. In this paper, we take the online theater reviews as the research object, obtain the review data of “Beyond the Clouds” through crawler, and use word cloud and word frequency analysis, positive-negative sentiment analysis, semantic network analysis and other methods to explore the sentiment information contained therein. The results show that moviegoers highly identify and recognize the real people and real deeds portrayed in such movies, and the content of user comments is basically dominated by positive emotions. Therefore, it is suggested that producers should pay attention to the relationship between the emotional tendency of film review data and film dissemination, and produce more films that reflect the mainstream ideology or that are close to the lives of ordinary viewers.

References

[1]
PICARD R W. Affective Computing [M].Cambridge: TheMITPress,2000.
[2]
LIU Z X, ZHANG D G, LUO G Z, A New Method of Emotional Analysis Based on CNN -BiLSTM Hybrid Neural Network [J].Cluster Computing,2020,23(4):2901-2913.
[3]
GHANEM B, ROSSO P, RANGEL F. An Emotional Analysis of False Information in Social Media and News Articles[J]. ACM Transactions on Internet Technology,2020,20(2): 1-18.
[4]
WANG Zhumei, HU Yanrong, LIU Hongjiu. Sentiment analysis of online reviews of agricultural products based on LDA topic model and intuitionistic fuzzy TOPSIS[J]. Data Acquisition and Processing,2020,35(5):965-977.
[5]
Ben Xu,Guoqing Xu,Zhiyu Cheng. Sentiment analysis of commodity reviews based on MGCNN[J]. Journal of Wuhan Engineering University,2020,42(5):585-590.
[6]
LIU Min,WANG Qianqian,LI Huizong. Sentiment analysis of online commodity reviews based on text mining[J]. Journal of Liaoning University of Technology(Natural Science Edition),2018,38(5):330-335.
[7]
YANG Shan,CHENG Key,YIQI Yao. Research on User Sentiment Analysis of Internet Public Opinion in Colleges and Universities Based on Text Mining[J]. Journal of Wuhan Textile University,2020,33(5):74-80.
[8]
ZHANG Yipeng,MA Jingdong. Research on audience sentiment analysis and communication characteristics of misleading information about public health emergencies[J]. Data Analysis and Knowledge Discovery,2020,4(12):45-54.
[9]
Ma Li,Gong Yulong. A review of text sentiment analysis research[J]. Electronic Science and Technology, 2018,27(11):180-184
[10]
Kuang Kaijin,Liao Hailin,Pei Wenqing. Emotional Analysis of Film Review Data Based on Text Mining——A case study of "MY PEOPLE, MY COUNTRY" [J]. Journal of Wuyi College, 2022,41(05):68-74.

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  1. Machine Learning Based Sentiment Analysis of Movie Reviews——A case study of “Beyond the Clouds”

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    CACML '24: Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine Learning
    March 2024
    478 pages
    ISBN:9798400716416
    DOI:10.1145/3654823
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 May 2024

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