Sentiment Analysis as a Tool of Linguistic Emotionology: Assessment of the Text Tonality Analysis Systems Potential

The assessment of text tone in large information flows is solved using both qualitative and quantitative methods. Qualitative methods include, primarily, the methods of linguistic emotionology, such as the compilation of tone dictionaries used in computer systems to evaluate the tone of a given text. the article discusses the principles of functioning of automatic text analysis systems as a method of computer-aided text analysis. it also provides an analysis of several modern tone analysis systems. characteristics of these systems are identified, and advantages and disadvantages are revealed based on linguistic material from marked-up film and product reviews from a well-known online marketplace. Special attention is given to linguistic reasons behind the challenges in assessing tone, such as multilingualism, different ways of presenting text by users, including abbreviated forms, can make the process difficult to understand. Genre diversity, implicit assessments, polysemy, homonymy, polarity modifiers, subjunctive mood, sarcasm, irony are all factors that can complicate the process of determining the tonality of a piece of text. Based on the results of our study, we conclude that programs using a hybrid method have the most effective functionality for detecting tonality. these programs are an important tool for linguistic emotionology and linguoconflictology, as they provide a necessary evaluative component. the research suggests possible approaches for optimizing the functioning of these programs. the study allows us to gain a better understanding of the challenges associated with detecting tonality in text and selecting sentiment analysis systems that operate on different principles. these systems not only solve practical problems related to sentiment analysis but also serve as a valuable source of material for research within the linguistic theory of emotions.