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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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Интернет-исследования: исторический обзор и анализ производства знания

Социология власти. 2018. Т. 30. № 3. С. 69–92.
Kolozaridi P.

This article problematizes Internet Studies as a sub-discipline in social research. Internet Studies is an interdisciplinary research field encompassing both academic and non-academic research focusing on the internet and societal issues. The key institutions where Internet Studies develop tend to either be university-based or independent. The article focuses on these organizations and aims to reconstruct their history and areas of research as well as the type of knowledge they produce. The first part of the article is more descriptive and historical, explicating how Internet Studies developed. The author suggests a classification of three key periods of Internet Studies development: the emergence, institutionalization and development of sub-fields, e.g. data science, digital research of different objects such as death, childhood, humanities, arts, and online-research. The key finding of this analysis is that in the internet studies there are no strict boundaries between the theoretical and empirical object. The researchers consider themselves to be co-producers of the internet. The second part of the article problematizes this type of knowledge that is constructed in internet studies, and this part is mostly based on interviews with researchers. The author brings out an idea, that internet studies does not have strict epistemological borders and strong theoretical or methodological limitations; it therefore cannot justifiably be called scientific. As such, the meaning of knowledge becomes problematic. To address this problem, the term “research knowledge” is introduced. This type of knowledge is not scientific, it does not pretend to be disciplinary and is the same inside and outside the organization and in its products. In conclusion, the findings of this research aim to contribute to the development of Internet Studies as a sub-discipline — a sub-discipline which does not aim to study an entity but a transformation of social life due to the internet

Research target: Media and Communications Sociology (including Demography and Anthropology Social Sciences
Priority areas: sociology
Language: Russian
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Keywords: internetсоциология знаниясоциология организацийsociology of knowledgesociology of organizationsInternet studiesинтернет-исследованияинтернет
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