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News
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.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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Многопараметрический анализ лингвистических данных в информационной системе «Семограф» (на примере исследования речевого поведения пользователей социальной сети)

Вестник Томского государственного университета. Филология. 2020. № 64. С. 5–29.
Белоусов К. И., Ерофеева Е. В., Баранов Д. А., Зелянская Н. Л., Shchebetenko S.

The aim of this article is to demonstrate the capabilities of the information system Semograph (http://semograph.org) as a tool for text content analysis when implementing a network approach to the organization of scientific research in linguistics. Semograph can be used for the analysis of text data, creation and/or annotation of language/text corpora, conducting, processing and analysis of psycholinguistic and sociolinguistic experiments, development of classifiers and thesauri, and solving other problems that arise when analyzing language material. Semograph implements the principles of a full research cycle, network distribution of research participants, a multi-user mode of operation and methodological pluralism. The possibilities of network organization of work in Semograph are shown on the example of a multiparametric analysis of speech behavior, social parameters and psychological characteristics of users of the social network VKontakte. The total volume of the automatically collected material is 18,126 utterances of 340 users who have completed a psychological survey of BFI, according to which results of the severity of the five psychological personal traits (extraversion vs. introversion, agreeableness vs. antagonism, conscientiousness vs. lack of direction,
neuroticism vs. emotional stability, openness vs. closedness to experience) are determined. For the analysis of the text material, a multi-level hierarchical classifier was developed that allows each expert-linguist to create and develop a separate classification branch (thus, the same material is considered by different experts from different points of view, and its multiparametric linguistic classification is created). This classification and specific user metadata (gender, psychological characteristics, etc.) provide the basis for constructing a model of interrelations between linguistic parameters of speech and socio-psychological characteristics of a person by means of interactive visual analytics. The article demonstrates these interrelations on the example of differences in the use of role and spatial deixis tools by extroverts and introverts, abusive and obscene lexical unites by users with a strong tendency for closedness and openness to experince, etc. The resulting model shows that the speech variability of texts is due to the interaction of psychological and gender characteristics of the informants, rather than a single act of these factors. In general, the article demonstrates that the information system Semograph allows, on the one hand, analyzing large arrays of texts with linguistic and extra-linguistic annotations, on the other hand, applying a network model of research organization that in the aggregate gives advantages in constructing models of fragments of linguistic and sociocultural reality
 

Research target: Psychology
Priority areas: humanitarian IT and mathematics
Language: Russian
DOI
Text on another site
Keywords: визуальная аналитикаvisual analyticsNetwork Sciencesocial network servicesinformation system Semographmultiparameter analysissemantic graph modellingсетевая наукасоциальные интернет-сервисыинформационная система "Семограф"многопараметрический анализграфосемантическое моделирование
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