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Subject
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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Фейк во спасение? Представления россиян о (не)приемлемости ложной информации

Журнал социологии и социальной антропологии. 2026. Т. 29. № 1. С. 100–117.
Kazun A. D.

The term "fake news" has entered not only academic discourse but also everyday language. Researchers highlight a wide range of negative consequences associated with disinformation. However, it remains unknown whether the public problematizes this situation and whether news audiences are willing to justify fake news in certain contexts. This study's empirical base comprises 119 semi-structured interviews conducted between March and May 2024, focusing on perceptions of fake news. While the interviews reveal a generally negative attitude towards the dissemination of fake news, respondents noted its relative acceptability under specific circumstances. These include situations where the misinformation is perceived as having no negative consequences for individuals or society (e.g., humor and satire), avoids adverse reactions to current events (e.g., panic), or yields positive outcomes (e.g., raising public awareness of significant issues, prompting constructive or socially desirable actions, serving as a tool of state policy, a "training ground" for critical thinking, or a means of combating false beliefs). However, such fake news must meet certain criteria: minimal factual distortion, extraordinary circumstances and infrequent dissemination, temporary nature with subsequent corrective information provided, and compliance with existing legislation. Reasoning regarding the (un)acceptability of fake news can be framed within ethical or pragmatic logics. In the former, respondents emphasize the impossibility of justifying disinformation through potential positive effects. In the latter, attempts are made to calculate the potential positive and negative consequences of fake news, with a willingness to endorse unethical measures linked to the perceived shortcomings of others—individuals susceptible to cognitive biases, false beliefs, and excessive emotionality.

Research target: Sociology (including Demography and Anthropology Media and Communications Political Science, International Relations, and Public Administration
Language: Russian
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DOI
Text on another site
Keywords: медиамассовые коммуникацииСМИmass communicationdisinformation mediaфейкдезинформацияfake newsфейковые новостипотребление новостейnews consumption
Publication based on the results of:
Dynamics of Consumer, Financial and Labor Behavior in Russians under the New Geopolitical Conditions (2025)
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