Method for Analyzing the Ukrainian Language Texts Sentiment Using Natural Language Processing
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Дата
2025
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Анотація
The paper focuses on intelligent sentiment analysis of text related to named entities. The proposed method combines a neural network-based natural language processing model, a lexical NLP library, and a Ukrainian sentiment dictionary. It provides results in the form of sentiment scores for named entities at the sentence and text levels, as well as an overall sentiment evaluation of the analyzed content. The relevance of the research is determined by the growing need for accurate sentiment analysis in the context of large-scale digital information flows. Identifying emotional attitudes toward specific persons, organisations, or events has essential applications in monitoring public opinion, brand perception, political discourse, and financial market analysis. The scientific novelty lies in developing and implementing a method that supports Ukrainian-language texts and
evaluates sentiment across negativity, neutrality, positivity, and emotionality dimensions. The practical significance is creating a software system capable of semantic sentiment analysis of textual content, achieving higher effectiveness than translation-based approaches. The developed method can analyze public opinion, social media reactions, market trends, and individual texts.
Опис
Ключові слова
named entity recognition, emotional tone, emotional tone detection, Stanza, VADER
Бібліографічний опис
Zalutska O.O. Method for Analyzing the Ukrainian Language Texts Sentiment Using Natural Language Processing. Information Control Systems and Intelligent Technologies. Advances and Applications. Monograph. Liha-Pres. 2025. P.122-137. ISBN 978-966-397-538-2