Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2025
Abstract
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.
Keywords
Chinese sentiment analysis, keyword co-occurrence analysis, subject, research methodologies, thematic trends
Discipline
Artificial Intelligence and Robotics | Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering
Publication
Artificial Intelligence Review
Volume
58
First Page
1
Last Page
37
ISSN
0269-2821
Identifier
10.1007/s10462-024-10988-9
Publisher
Springer
Citation
WANG, Zhaoxia; HUANG, Donghao; CUI, Jingfeng; ZHANG, Xinyue; HO, Seng-Beng; and CAMBRIA, Erik.
A review of Chinese sentiment analysis: Subjects, methods, and trends. (2025). Artificial Intelligence Review. 58, 1-37.
Available at: https://ink.library.smu.edu.sg/sis_research/9928
Copyright Owner and License
Authors-CC-BY
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s10462-024-10988-9
Included in
Artificial Intelligence and Robotics Commons, Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons
