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News
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.
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.

 

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Ranking journals using social choice theory methods: A novel approach in bibliometrics

Journal of Informetrics. 2018. Vol. 12. No. 2. P. 416–429.
Subochev A., Fuad Aleskerov, Pislyakov V.

We use data on economic, management and political science journals to produce quan- titative estimates of (in)consistency of the evaluations based on six popular bibliometric indicators (impact factor, 5-year impact factor, immediacy index, article influence score, SNIP and SJR). We advocate a new approach to the aggregation of journal rankings. Since the rank aggregation is a multicriteria decision problem, ranking methods from social choice theory may solve it. We apply either a direct ranking method based on the majority rule (the Copeland rule, the Markovian method) or a sorting procedure based on a tournament solution, such as the uncovered set and the minimal externally stable set. We demonstrate that the aggregate rankings reduce the number of contradictions and represent the set of the single-indicator-based rankings better than any of the six rankings themselves.

Research target: Computer Science Mathematics Sociology (including Demography and Anthropology
Priority areas: IT and mathematics
Language: English
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DOI
Text on another site
Keywords: коллективный выборsocial choiceмногокритериальный выборимпакт-факторimpact factorexternally stable setвнешнеустойчивое множествоправило большинстваправило КоупландаSNIPSJRrank aggregationmajority ruleCopeland ruletournament solutionагрегирование ранжированийтурнирное решениеordinal methodmultiple criteriaординальный метод
Publication based on the results of:
Modern context of decision making and data analysis methods: human factor, uncertainty, risks, network models, big data (2018)
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