N. Manteyeva2024-01-162024-01-162022N. Manteyeva / FAST AND RELATIVELY ACCURATE SENTIMENT ANALYSIS FOR THE KAZAKH LANGUAGE / 2022 International Young Scholars' Conferencehttps://repository.sdu.edu.kz/handle/123456789/1125Abstract This paper constructs a fast and accurate sentiment analysis model for the Kazakh language. The main method for text classification is based on TF-IDF-based tokens trained with Logistic Regression. The processing and modeling stages are fully implemented in the PySpark framework. The proposed method has shown an accuracy level of 82% on an evenly distributed test dataset. As a byproduct of the work, we have collected a list of words in the Kazakh language that could signal the negativity/positivity of the given review.ensentiment analysisnatural language processingKazakh language2022 International Young Scholars' Conference№11Other