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July 9, 2026
HSE Economists Use Search Queries to Forecast Birth Rates
Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.
July 8, 2026
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Around one-third of Russians (31.3%) rarely eat out or buy ready-made meals. The core group of active consumers—those who eat out or purchase prepared food almost every day or several times a week—accounts for only about 9% of the population. These are the findings of a study conducted by the HSE Institute for Social Policy. According to the researchers eating out is no longer a marker of high social status in Russia.
July 8, 2026
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HSE University and the Russia Renewable Energy Development Association (RREDA) have signed a partnership and information cooperation agreement to support Renewable Energy of the Planet—2026, a national competition with international participation for students and early-career researchers. Applications are open on the competition's website until September 20, 2026.

 

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In search of soft power: mapping the expert community with a bibliometric network analysis

Journal of political power. 2022. Vol. 15. No. 3. P. 556–571.
Alina V. Vladimirova

Soft power is one of the most influential concepts in the discipline of international relations, yet it is highly criticized for ambiguity and analytical weakness. Thus, through thoughtful literature reviews, scholars continue with clarifying and mapping the theory within a broader political power research programme. It is in this scholarly context that this article offers tools from a bibliometric network analysis that could be useful in understanding scholarly approaches to soft power. The constructed network of authors with edges representing connections set on keywords allows us to demonstrate the place of the soft power expert community and the proximity of corresponding research interests.

Research target: Political Science, International Relations, and Public Administration
Language: English
DOI
Text on another site
Keywords: soft powernetwork analysisbibliometric analysiscommunity detectionlatent space model
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