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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Избегание новостей в России: Масштабы и характерные черты

Вестник Московского университета. Серия 10: Журналистика. 2025. Т. 50. № 1. С. 69–93.
Kazun A. D.

This article explores the phenomenon of news avoidance in Russia during 2023-2024, drawing on data from a survey of 6,007 respondents and 67 interviews. The study reveals that over 20% of Russians consciously limit their news consumption, indicating that a significant portion of the population engages in news avoidance, although it is less widespread than in many other countries. The most commonly avoided topics include politics, international relations, crime, and economics. The primary reasons for avoiding news are its negative impact on mood, an oversaturation of political content, news fatigue, and distrust in the media. Women are more likely than men to cite emotional reasons for avoiding news. That may be connected with gender stereotypes and socialization differences. The strategies for news avoidance are varied, with the most common approaches involving the reduction of the number of used news sources and the time spent on them, or redirecting attention to alternative activities. News consumption regulation predominantly occurs through self-restriction and conscious habit adjustment rather than changing of the information environment. While news avoidance is often intended to preserve mental health, individuals who limit their news intake tend to exhibit higher levels of emotional distress.

Research target: Sociology (including Demography and Anthropology Media and Communications Political Science, International Relations, and Public Administration
Language: Russian
Full text
DOI
Text on another site
Keywords: медиановостимедиапотреблениеmedia consumptionnews avoidanceизбегание новостейдоверие новостям
Publication based on the results of:
Consumption and economic behavior of households in Russia, 2025-2027 (2027)
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