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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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Мемы как инструмент консолидации протестного движения (на примере коротких видео социальной сети TikTok)

Мониторинг общественного мнения: Экономические и социальные перемены. 2021. № 6. С. 76–96.
Poretskova A., Savin N.

Internet-memes have already become a habitual element of the new media environment. The majority of scholars focus on humoristic images and how they contribute to racist stereotypes and untrust to the political process among internet users. In this paper, we consider how TikTok short videos contribute to protest movement consolidation. Based on an empirical dataset of 65 videos, which broadcast 2020 Khabarovsk protest rallies, the article investigates peculiarities of memes’ structural patterns, what functions memes may carry out in the context of the protest movement, and what symbolic structures dominate social platform’s space. The methodological framework is based on the visual analysis of frames with the scope of semiotic and discursive levels of visual interpretation. Due to the fact that TikTok creates pre-political publiс spaces, short videos highlight the necessity of participation in protest rallies, rather than a clarification of demands. There are three other notable features of TikTok memes - the lack of attention to political enemies, the combination of populist images and regional symbols, and the general lack of symbolic content.

Research target: Media and Communications Political Science, International Relations, and Public Administration
Language: Russian
DOI
Keywords: новые медиаполитические коммуникацииpolitical communicationпротестное движениемемыvisual framingвизуальный фреймингmemes new mediaTikTokTikTokprotect activity
Publication based on the results of:
Political mobilisation in the context of communicative abundance (2021)
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