COMPARATIVE EFFECTIVENESS OF RULE-BASED AND MACHINE LEARNING METHODS IN SENTIMENT ANALYSIS OF KAZAKH LANGUAGE TEXTS

COMPARATIVE EFFECTIVENESS OF RULE-BASED AND MACHINE LEARNING METHODS IN SENTIMENT ANALYSIS OF KAZAKH LANGUAGE TEXTS

Sentiment analysis is increasingly pivotal in natural language processing (NLP), crucial for deciphering public opinions across diverse sectors. This research conducts a comparative examination of rule-based and machine learning (ML) methods in sentiment analysis, specifically targeting the Kazakh l...

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Bibliographic Details
Main Authors: Mukhtar Amirkumar, Kamila Orynbekova, Assem Talasbek, Dauren Ayazbayev, Selcuk Cankurt
Format: Article
Language:English
Published: Astana IT University 2024-03-01
Series:Scientific Journal of Astana IT University
Subjects:
sentiment analysis
machine learning
rule-based approach
logistic regression
multinomial naive bayes
Online Access:https://journal.astanait.edu.kz/index.php/ojs/article/view/467

Internet

https://journal.astanait.edu.kz/index.php/ojs/article/view/467

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