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Subject
News
October 19, 2026
'Cultural Studies Seeks to Understand What Lies Beneath the Surface of Everyday Things'
Maxim Zhiganov has been exploring different aspects of sound for many years—first in relation to his native Perm and then on a broader, global scale. In this interview for the HSE Young Scientists project, he talks about sound maps, the special issue of the journal Logos, and why it is important to make the familiar less clear and obvious.
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.

 

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Методологические основы анализа ценностных ориентаций в российском сегменте социальных сетей

Медиалингвистика. 2026. Т. 2. № 13.
Zverev S., Соколова Е. Н., Grigoreva M., Smirnov A.

The article presents a comprehensive methodology for analysing value orientations within the Russian segment of social networks, validated on a corpus exceeding two million posts. All research stages are described, from data collection using the Brand Analytics monitoring system and lexical preprocessing of texts (normalisation and cleaning) to topic modelling with Latent Dirichlet Allocation (LDA), clustering of value‐related topics (word–embedding representations combined with the k–means algorithm), and subsequent manual validation of the resulting clusters. The analysis yields a “map” of 25 value clusters, among which patriotism, love, family, mutual aid, and support are dominant. The findings reveal the prevalence of social values (patriotism, family, support) alongside a considerable share of self–actualisation values (success, achievement). The significance of the results for the sociology of values is discussed, along with practical applications: monitoring the dynamics of societal value orientations, informing information policy, advancing the national goal of fostering patriotic and socially responsible individuals, and designing educational programmes and communication strategies.

Research target: Media and Communications
Language: Russian
DOI
Text on another site
Keywords: ценностные ориентациисоциальные сетикластеризацияvalue orientationsclusterizationlatent Dirichlet allocationLatent Dirichlet Allocation (LDA)тематическое моделированиеsocial nets topic modelling
Publication based on the results of:
Modern Technologies of Socio-Political Communication (2025)
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