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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Психолингвистический анализ непрофессионального дискурса о коррупции в социальной сети в «ВКонтакте»

Мониторинг общественного мнения: Экономические и социальные перемены. 2026. № 1. С. 231–250.
Кузнецова Ю. М., Maksimenko A., Станкевич М. А., Смирнов И. В.

The article is devoted to the analysis of the non-professional online discourse on corruption presented on the social network VKontakte. Unlike the institutional or expert approach, the focus on everyday, user-generated reflection allows you to capture the deep values, forms of expression and linguistic patterns of everyday morality, which is especially important in the context of the growing importance of social networks as a source of information and the formation of public sentiment. The aim of the study was to determine the psycholinguistic characteristics of non-professional discourse on corruption, including the degree of involvement of participants, the ratio of emotional and rational components, evaluative trends and thematic focus. The empirical base consisted of 59,297 user comments, divided into three subcorps: corrupt (19,804 comments), medical (19,493 comments) and background, neutral (20,000 comments). 
Text processing was carried out using the TITANIS intelligent analysis tool, which provides multi-level identification of linguistic and semantic markers, such as emotional coloring, categoricity, stylistic orientation and frequency of thematic units. To assess the significance of the differences, the Mann-Whitney U-test was used for data close to a normal distribution and the chi-square criterion for abnormally distributed ones, while rare vocabulary markers were binarized (0 – absence, 1 – presence). The Bonferroni correction was used to prevent the first kind of error in multiple comparisons.
The results showed that unprofessional discourse on corruption is characterized by high emotional intensity, dominance of negative tone and political focus with little attention to economic issues. Discussions are characterized by decreased rationality and low communicative engagement, with frequent use of cliched expressions and radical sentences. It is shown that the unprofessional discourse on corruption demonstrates stable psycholinguistic features indicating the moral and emotional positions of the authors. The statements of the participants in the discussions on corruption are characterized by pronounced condemnation, expressions of group solidarity and contradictory moral attitudes, where anger and pessimism are combined with radical calls for justice. However, low communicative engagement and avoidance of personal experience indicate that this morality serves more as a tool for public criticism and social identification than as a basis for deep moral analysis or dialogue.

Research target: Psychology Media and Communications Philology and Linguistics
Language: Russian
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Text on another site
Keywords: социальные сетиобработка естественного языка social mediaотношение к коррупцииattitudes towards corruption natural language processingnon-professional discourse on corruptionpsycholinguistic indicators of the textнепрофессиональный дискурс о коррупциипсихолингвистические показатели текста
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