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News
July 24, 2026
‘I Like Self-Fulfilling Prophecies
Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
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.

 

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Взаимосвязь сетевых характеристик и субъектности сетевых сообществ в социальной сети Твиттер

Вопросы кибербезопасности. 2020. Т. 37. № 3. С. 40–57.
Chepovskiy A., Воронин А. Н., Ковалева Ю. В.

The purpose of the study: analysis of the graph of interacting objects of social networks based on the selection of implicit communities, assessment of the subjectivity of the selected communities and comparison of the network characteristics of communities and various indicators of their subjectivity.

Method: communities detection on the constructed weighted graph of a social network, psycholinguistic analysis of community content using a list of discourse markers of subjectivity, statistical methods for identifying the relationship between network characteristics and the frequency of discourse markers.

Results: algorithms to construct a graph and to import user attributes were developed, an algorithm for dividing a weighted graph into implicit user communities was implemented, the subjectivity of the content of the selected network communities in the social network Twitter has was assessed, the relationship and directional shift in the connectivity of the graph and various indicators of the subjectivity of the network community were identified.

Research target: Computer Science Psychology
Priority areas: IT and mathematics
Language: Russian
Full text
DOI
Keywords: social subjectivitysocial network analysisnetwork communityвыделение сообществанализ социальной сетиdiscourse markersдискурсивные маркерысоциальный графgraph community detection
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