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  • Схожесть или близость? Структура социальных связей школьников в масштабе области
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June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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Схожесть или близость? Структура социальных связей школьников в масштабе области

Городские исследования и практики. 2020. Т. 4. № 1. С. 88–104.
Dokuka S., Smirnov I., Dementeva J.

There are two factors that are generally considered key in the formation of social networks. One is homophily or the tendency of similar individuals to connect with each and the other is geographical proximity. The roles of homophily and proximity, however, are rarely compared. This means that there are no good estimates of the relative importance of these two mechanisms. We use data from 631 schools of the Samara and Tomsk regions to compare the role of homophily by academic performance and interests with the role of geographical proximity in the formation of online social ties between students from different schools. We analyzed information on friendship ties between 20,000 users of VKontakte (the most popular social networking site in Russia) from these schools. We find that geographical proximity is the key factor in the formation of social ties: the probability of a friendship tie between geographically close schools is high (60–85%), but it rapidly decreases with distance and is less than 5% for schools that are far apart from each other. We also find that homophily plays a less important role although similarity in interests has a higher predictive power for the probability of a friendship tie than similarity in academic performance. The results are similar for both regions, which might indicate their universal nature.
Our results indicate that, even in the digital age, the key factor in the formation of social ties is proximity while homophily determines social ties to a lesser extent.

Research target: Sociology (including Demography and Anthropology Education
Priority areas: sociology
Language: Russian
Text on another site
Keywords: социальные сетиsocial networksproximityHomophilyгеографическая близостьVkontaktefriendship networksсети дружбыВКонтактегомофилия
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