Practical Implementation of Neural Network Method for Stress Features Detection by Social Internet Networks Posts

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dc.contributor.authorMazurets, O.V.
dc.contributor.authorSobko, O.V.
dc.contributor.authorMolchanova, M.O.
dc.contributor.authorZalutska, O.O.
dc.contributor.authorYurchak, A.V.
dc.contributor.authorМазурець, Олександр Вікторович
dc.date.accessioned2024-12-10T18:18:21Z
dc.date.available2024-12-10T18:18:21Z
dc.date.issued2024
dc.description.abstractThe article considers a neural network method for stress features detection by social internet network posts, designed for automated analysis of text messages posted on social networks in order to identify signs of stress in posts. Based on the designed functional and design architectures of the information system for detecting stress in posts, the software implementation was carried out to study the effectiveness of the developed neural network method for stress features detection by social internet network posts. The practical implementation of the neural network method has determined that the developed method allows detecting stress features in social Internet network posts with an accuracy of 90%.
dc.identifier.citationMazurets O.V., Sobko O.V., Molchanova M.O., Zalutska O.O., Yurchak A.V. Practical Implementation of Neural Network Method for Stress Features Detection by Social Internet Networks Posts. Global Science: Prospects and Innovations. Proceedings of the II International Scientific and Theoretical Conference «Scientific Review of the Actual Events, Achievements and Problems». May 31, 2024. Berlin, Federal Republic of Germany: International Center of Scientific Research. 2024. Pp. 160-167.
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/17213
dc.language.isoen
dc.titlePractical Implementation of Neural Network Method for Stress Features Detection by Social Internet Networks Posts
dc.typeСтаття
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