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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Геолокация в исследовательских целях: геометки как источник данных

ИНТЕРакция. ИНТЕРвью. ИНТЕРпретация. 2020. Т. 12. № 2. С. 65–80.
Strelnikova A., Бурова А. А.

The worldwide spread of social networks provides new opportunities to collect data for various applied research. The geotagging function, which is present in most social networks, is extremely useful in the case of spatial research. For urban researchers, this is more than just an opportunity to collect a huge amount of information about the behavior of people in space, but also to analyze the space itself. However, this type of data has both significant advantages and limitations. The article includes highlighting the most significant characteristics that urban researchers need to consider working with social networks: their volume (the ability to work with them as big data), non-reactivity (they are reproduced by the users themselves) and additional interpretations (they allow us to understand the meanings of certain elements of space for individual individuals or groups). The authors also illustrate the research opportunities provided by online data in combination with geotagging with various empirical examples.

Research target: Sociology (including Demography and Anthropology
Priority areas: sociology
Language: Russian
Full text
DOI
Text on another site
Keywords: социальные сетиurban studiesгеолокациягородские исследованияsocial networkgeolocationgeotaggingонлайн-данныегеометкагеотеггинг
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