A review of Chinese sentiment analysis: Subjects, methods, and trends
Sentiment analysis has emerged as a prominent research domain within the realm of natural language processing, garnering increasing attention and a growing body of literature. While numerous literature reviews have examined sentiment analysis techniques, methods, topics and applications, there remai...
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sg-smu-ink.sis_research-109282025-01-10T07:20:01Z A review of Chinese sentiment analysis: Subjects, methods, and trends WANG, Zhaoxia HUANG, Donghao CUI, Jingfeng ZHANG, Xinyue HO, Seng-Beng CAMBRIA, Erik Sentiment analysis has emerged as a prominent research domain within the realm of natural language processing, garnering increasing attention and a growing body of literature. While numerous literature reviews have examined sentiment analysis techniques, methods, topics and applications, there remains a gap in the literature concerning thematic trends and research methodologies in sentiment analysis, particularly in the context of Chinese text. This study addresses this gap by presenting a comprehensive survey dedicated to the progression of research subjects, methods and trends in sentiment analysis of Chinese text. Employing a framework that combines keyword co-occurrence analysis with a sophisticated community detection algorithm, this survey offers a novel perspective on the landscape of Chinese sentiment analysis research. By tracing the interplay between research methodologies and emerging topics over the past two decades, our study not only facilitates a comparative analysis of their correlations but also illuminates evolving patterns, identifying significant hotspots and trends over time for Chinese language text analysis. This invaluable insight provides a roadmap for researchers seeking to navigate the intricate terrain of sentiment analysis within the context of Chinese language. Moreover, this paper extends beyond the academic realm, offering practical insights into sentiment analysis methodologies and themes while pinpointing avenues for future exploration, technical limitations, and directions for sentiment analysis of Chinese text. 2025-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/9928 info:doi/10.1007/s10462-024-10988-9 https://ink.library.smu.edu.sg/context/sis_research/article/10928/viewcontent/2025_A_review_of_Chinese_sentiment_analysis__subjects__methods__and_trends.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Chinese sentiment analysis keyword co-occurrence analysis subject research methodologies thematic trends Artificial Intelligence and Robotics Databases and Information Systems Numerical Analysis and Scientific Computing |
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Chinese sentiment analysis keyword co-occurrence analysis subject research methodologies thematic trends Artificial Intelligence and Robotics Databases and Information Systems Numerical Analysis and Scientific Computing WANG, Zhaoxia HUANG, Donghao CUI, Jingfeng ZHANG, Xinyue HO, Seng-Beng CAMBRIA, Erik A review of Chinese sentiment analysis: Subjects, methods, and trends |
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Sentiment analysis has emerged as a prominent research domain within the realm of natural language processing, garnering increasing attention and a growing body of literature. While numerous literature reviews have examined sentiment analysis techniques, methods, topics and applications, there remains a gap in the literature concerning thematic trends and research methodologies in sentiment analysis, particularly in the context of Chinese text. This study addresses this gap by presenting a comprehensive survey dedicated to the progression of research subjects, methods and trends in sentiment analysis of Chinese text. Employing a framework that combines keyword co-occurrence analysis with a sophisticated community detection algorithm, this survey offers a novel perspective on the landscape of Chinese sentiment analysis research. By tracing the interplay between research methodologies and emerging topics over the past two decades, our study not only facilitates a comparative analysis of their correlations but also illuminates evolving patterns, identifying significant hotspots and trends over time for Chinese language text analysis. This invaluable insight provides a roadmap for researchers seeking to navigate the intricate terrain of sentiment analysis within the context of Chinese language. Moreover, this paper extends beyond the academic realm, offering practical insights into sentiment analysis methodologies and themes while pinpointing avenues for future exploration, technical limitations, and directions for sentiment analysis of Chinese text. |
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text |
author |
WANG, Zhaoxia HUANG, Donghao CUI, Jingfeng ZHANG, Xinyue HO, Seng-Beng CAMBRIA, Erik |
author_facet |
WANG, Zhaoxia HUANG, Donghao CUI, Jingfeng ZHANG, Xinyue HO, Seng-Beng CAMBRIA, Erik |
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WANG, Zhaoxia |
title |
A review of Chinese sentiment analysis: Subjects, methods, and trends |
title_short |
A review of Chinese sentiment analysis: Subjects, methods, and trends |
title_full |
A review of Chinese sentiment analysis: Subjects, methods, and trends |
title_fullStr |
A review of Chinese sentiment analysis: Subjects, methods, and trends |
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A review of Chinese sentiment analysis: Subjects, methods, and trends |
title_sort |
review of chinese sentiment analysis: subjects, methods, and trends |
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Institutional Knowledge at Singapore Management University |
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2025 |
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https://ink.library.smu.edu.sg/sis_research/9928 https://ink.library.smu.edu.sg/context/sis_research/article/10928/viewcontent/2025_A_review_of_Chinese_sentiment_analysis__subjects__methods__and_trends.pdf |
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