Abstract
With the growing number of social and online sales platforms, the comments and reviews posted on these platforms play a significant role in choosing products and services. Nowadays, consumers actively search for and read reviews left by other customers on online shopping sites before purchasing a particular product or service. And product manufacturers receive valuable feedback on the quality of their goods and services. Therefore, it is very important to take your place in the market and maintain it in a period when technologies are developing and rapidly evolving every day. Organizations do not need to conduct typical surveys to collect public opinion on their products and services, as this information is now available in open sources. To extract valuable information from customer reviews, opinion and sentiment analysis methods based on natural language processing are used. Opinions are divided into two types: non-comparative (regular) and comparative. Using advanced Natural Language Processing methods and machine and deep learning models, it is possible to automate the collection and analysis of comparative opinions, allowing businesses and researchers to make decisions based on comparable data. This paper provides a review of comparative opinion mining and sentiment analysis in the Kazakh language. Due to the limited availability of articles specifically addressing comparative opinion mining in Kazakh, we broadened our review to include related research in sentiment analysis overall. Additionally, the article discusses the structure of comparative sentences in both English and Kazakh, providing insights into linguistic frameworks.