Chinese text-oriented sentiment analysis models, corpus, and recent advances

Sentiment analysis of Chinese text presents unique challenges due to the distinct characteristics of the Chinese language, including cultural nuances, word formation styles, and the dynamic nature of certain terms on social media. This paper reviews recent methods for Chinese sentiment analysis, which can be broadly classified into three categories: dictionary-based, traditional machine learning-based, and advanced deep learning-based. A comparative analysis highlights the strengths and limitations of each method across various applications. Additionally, commonly used Chinese corpora, sentiment analysis systems and tools are introduced. Furthermore, this paper discusses the potential directions for future research, such as recognising complex sentiment states, multimodal sentiment analysis, and cross-cultural sentiment analysis.