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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.
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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.
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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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Network Analysis of Players Transfers in eSports: The Case of Dota 2

P. 468–473.
Ekaterina Marchenko, Vsevolod Suschevskiy

In this work, we analyse the structure of local and regional market of player transfers in popular eSports discipline Dota 2. Together with team performance metrics, these data provide us with an opportunity to model network of transfers between teams. In turn, the transfers show the actual structure of mobility in the industry. We collected the data on players’ transfers for the top professional teams and their transfer partners, based on transactions between two world tournaments: The International 16 to The International 17. We built a directed network of transfers and analysed centralities, assortative mixing, and link formation.

The global transfer market structure is organised around continental regions. At the same time, teams with the same level of performance rarely have transfers. This can be a reliable indicator of the presence of mobility lifts, in this case, mastodons of the tournament accept in their ranks natives of the less rated teams. On the other hand, some successful players may leave the best teams to establish their own, in the same way as top managers leave the large corporations to launch startups.

Language: English
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Keywords: сетиsocial network analysisnetworkseSportsкиберспортсоциально-сетевой анализ
Publication based on the results of:
Социальные алгоритмы: онлайн-сообщества, рейтинги, сети, рекомендации (2017)

In book

Digital Transformation and Global Society Third International Conference, DTGS 2018, St. Petersburg, Russia, May 30 –June 2, 2018, Revised Selected Papers, Part I
Digital Transformation and Global Society Third International Conference, DTGS 2018, St. Petersburg, Russia, May 30 –June 2, 2018, Revised Selected Papers, Part I
Issue 858. , Cham: Springer, 2018.
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