Method for Analyzing the Ukrainian Language Texts Sentiment Using Natural Language Processing

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dc.contributor.authorZalutska, O.O.
dc.date.accessioned2025-10-26T20:05:35Z
dc.date.available2025-10-26T20:05:35Z
dc.date.issued2025
dc.description.abstractThe 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.
dc.identifier.citationZalutska 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
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/19734
dc.language.isoen
dc.subjectnamed entity recognition
dc.subjectemotional tone
dc.subjectemotional tone detection
dc.subjectStanza
dc.subjectVADER
dc.titleMethod for Analyzing the Ukrainian Language Texts Sentiment Using Natural Language Processing
dc.typeСтаття
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