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News
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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?

Anti-vaccination Movement on VK: Information Exchange and Public Concern

P. 108–121.
Petrov I.

Vaccination is a simple yet effective method for controlling the spread of communicable diseases. However, an increasing number of individuals are expressing distrust in the vaccination process and are choosing not to vaccinate themselves or their children. One explanation suggests that such doubtfulness is maintained through widespread misinformation available on social media. This research takes an exploratory approach to the anti-vaccination communities in the Russian social network VK. It applies network analysis to identify patterns in the dissemination of information and text mining to capture general public concern shown through the language of the posts published. In total, the digital fields of 135 open communities were analyzed. Textual data, public information about communities as well as reposts were collected using API technology. The findings revealed a hierarchical structure within the network of communities, indicating that larger and more active communities control the flow of information. Additionally, public concerns regarding vaccination were linked to fears of vaccine complications, parental anxieties, and uncertainties about the effects on the body.

Language: English
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Keywords: социальные сетитекстовый анализсетевые исследованияRussian Social Mediaanti-vaccination movementАнтивакцинаторство text miningSocial network analysis (SNA)

In book

Digital Transformation and Global Society. 6th International Conference, DTGS 2021, St. Petersburg, Russia, June 23–25, 2021, Revised Selected Papers
Springer, 2022.
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