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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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Aggression in Digital Interactions: The Effect of Toxicity in Online Gaming Communication

Journal of Content, Community and Communication. 2025. Vol. 23. Article 5.
Iuliia Naidenova, Parshakov P., Matkin N.

This study analyzes the computer mediated text communication of non-professional video game players. The purpose of this study is to identify the impact of player communication toxicity on team performance. The dataset comprises 42,720 matches played between November 5 and November 18, 2015, including game statistics and chat messages. We use a BERT-model to classify toxicity of messages. Then regression analysis was used to estimate the impact of toxic behavior on winning probability and game satisfaction. The results indicate that the highest winning probability of a team corresponds to a low number of toxic messages in team communication, low average toxicity of communication, but high variation in toxicity levels. Furthermore, low levels of toxicity in communication can enhance overall game satisfaction.

Research target: Economics and Management Media and Communications
Language: English
Full text
DOI
Text on another site
Keywords: logistic regressioneSportsDota 2Team performancetoxic behavior
Publication based on the results of:
Strategic behavior of companies and individuals under conditions of technological transformation in Russia (2025)
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