Nowadays, extensive scientific research is being carried out in the field of sentiment analysis within global linguistics. There are several types of sentiment analysis, among which aspect-based sentiment analysis (ABSA) is gaining popularity. Unlike other types of sentiment analysis, ABSA provides a separate emotional evaluation for each aspect in a text. This article provides a comprehensive analysis of the scientific studies conducted on sentiment analysis in the Uzbek language. Sentiment analysis is one of the key areas of natural language processing and serves to detect positive, negative, or neutral sentiments in texts. The article reviews the current research on sentiment analysis in Uzbek, the main methodologies used for SA, including lexicon-based approaches, machine learning algorithms, and deep learning technologies. Additionally, the current state of research, existing challenges, and future prospects are analyzed. This study lays a theoretical and practical foundation for the development of scientific work in the field of sentiment analysis in the Uzbek language, the implementation of modern technologies, and more effective analysis of texts in our language.

Uzbek language, sentiment analysis, natural language processing, machine learning, linguistics, text analysis, neural networks.

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