The purpose of research is to increase the level of specification of sentiment within the framework of sentiment analysis of Russian-language texts by developing a dataset with an extensive set of emotional categories. The paper discusses the main methods of sentimental analysis and the main emotional models. A software system for decentralizing data tagging has been developed and described. The novelty of this work lies in the fact that to determine the emotional coloring of Russian-language texts, an emotional model is used for the first time, which contains more than 8 emotional classes, namely the model of R. Plutchik. As a result, a new dataset was developed for the study and analysis of emotions. This dataset consists of 24,435 unique records labeled into 32 emotion classes, making it one of the most diverse and detailed datasets in the field. Using the resulting dataset, a neural network was trained that determines the author’s set of emotions when writing text. The resulting dataset provides an opportunity for further research in this area. One of the promising tasks is to enhance the efficiency of neural networks trained on this dataset.

Keywords: sentiment, analysis, model, Robert Plutchik, emotions, markup, text

Eye tracking (oculography) is a technology that allows recording the direction of human gaze on a visual stimulus. It’s application can provide researchers with valuable data on which elements of the environment are most attractive in various contexts, in areas such as marketing, psychology, etc. The aim of this work is to identify the pattern of human attention distribution on visual stimulus objects of different sizes using eye tracking technology. A webcam was used to record the subjects’ gaze movements while they were studying experimental images. The results of the experiments showed that larger objects in visual stimuli receive higher attention priority than smaller objects. This observation is true for both human-created works and images created by artificial intelligence (Kandinsky 3.1 is used in this study). The obtained results of the study will improve our understanding of how people perceive visual information, which can contribute to the creation of more effective approaches to interface development.

Keywords: eye tracking technology, attention priority, region of interest, number of eye gaze registrations, artificial intelligence, Vincent Van Gogh