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September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.

 

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Анализ текстов сообществ социальных сетей

Успехи кибернетики. 2023. Т. 4. № 2. С. 33–39.
Аванесян Н. Л., Зенькова В. В., Chepovskiy A., Chepovskiy A.

In this paper the authors describe the methodology for the statistical analysis of texts in the network of Telegram channels based on comparison of automatically generated frequency dictionaries by methods of correlation analysis. Coefficients of pairwise rank correlation are considered for comparing the frequency characteristics of texts in natural language. The method is proposed to assess the quality of the implicit communities extraction on the graph obtained by importing data from the channel network of the Telegram messenger.

Research target: Mathematics Computer Science
Language: Russian
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Keywords: анализ социальных сетейчастотный словарьfrequency dictionaryrank correlationsранговая корреляцияsocial networks analysisautomated text analysisавтоматический анализ текстовcommunities of graphнеявные сообщества графов
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