PROSPECTS OF DIGITAL SENTIMENT ANALYSIS IN THE STUDY OF THE KAZAKH SHORT PROSE GENRE

Abstract

This article explores the potential of digital sentiment analysis in studying the genre of short prose in Kazakhstan. It focuses on the application of computational methods, such as sentiment analysis, to uncover and quantitatively assess the emotional tones embedded in literary texts. Specifically, the study examines Dulat Isabekov's play "Transit Passenger,"using computational algorithms to investigate emotional transitions and their relationship with narrative structures. Digital tools offer new possibilities for identifying hidden emotional patterns, providing deeper insights into the cultural and social shifts reflected in Kazakh literature during the post-Soviet transformation period. The analysis demonstrates that the use of digital technologies in literary studies opens up new horizons, offering more objective and quantitative approaches to the exploration of emotions in literature.