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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
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You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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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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DOI
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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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