A Review of Aspect Level Sentiment Analysis

Aspect-level sentiment analysis is an important text sentiment analysis technology. It can perform fine-grained calculation and analysis of the sentiment of specific aspects in the text, thereby helping people understand the sentiment of the text more comprehensively. This technology finds extensive application in real-life scenarios such as recommender systems and question answering systems. This article first introduces the application background and application scenarios of aspect-level sentiment analysis, then discusses the importance of data set selection and factors that need to be considered when selecting data sets, and then explains the specific process of aspect-level sentiment analysis, including data preprocessing, Steps such as aspect extraction and sentiment classification are also introduced. Common analysis techniques, such as dictionary matching, are also introduced. Through the application of these methods, aspect-level sentiment analysis can provide richer and more fine-grained sentiment information, thereby providing strong support for research and applications in related fields. However, aspect-level sentiment analysis also faces many challenges, such as how to deal with negative emotional expressions and how to deal with non-emotional expressions. This article finally discusses the development trends and opportunities of aspect-level sentiment analysis.