Chinese Sentiment Analysis Based on Knowledge Graph

With the rapid development of data mining technology, the use of knowledge graph for Chinese sentiment analysis has become a research hotspot in the field of natural language processing. This article aims to explore the combination of knowledge graph technology and Chinese sentiment analysis to enhance the depth and accuracy of sentiment analysis. It outlines the development trajectory and technical framework of knowledge graph, explains the theoretical foundation of sentiment analysis methods, and proposes relevant challenges and solutions based on the uniqueness of Chinese language. Building on the knowledge graph for sentiment analysis, this article designs an empirical research plan and reveals the practical application effects through rigorous data analysis. The research results show that knowledge graph can effectively improve the accuracy of Chinese sentiment analysis and the ability to handle complex texts. The article summarizes the innovations of the research and expectations for future work, providing theoretical basis and practical guidance for subsequent research.