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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
‘I Would Like My Research to Help Make the World a Calmer and Better Place
Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Неологизмы в социальной сети Фейсбук

Компьютерная лингвистика и интеллектуальные технологии. 2014. С. 440–454.
Obiedkov S., Панченко А. И., Muraviev N.

*Реализация соц. сети Facebook запрещена на территории России по основаниям осуществления экстремистской деятельности.

In this paper, we present a study of neologisms and loan words frequently occurring in Facebook user posts. We have collected a dataset of over 573 million posts written during 2006-2013 by Russian-speaking Facebook users. From these, we have built a vocabulary of most frequent lemmatized words missing from the Opencorpora dictionary (http://opencorpora.org/dict.php) the assumption being that many such words have entered common use only recently. This assumption is certainly not true for all the words extracted in this way; for that reason, we manually filtered the automatically obtained list in order to exclude non-Russian or incorrectly lemmatized words, as well as words recorded by other dictionaries or those occurring in pre-2000 texts from the Russian National Corpus (http:// www.ruscorpora.ru). The result is a list of 168 words that can potentially be considered neologisms. We present an attempt at an etymological classification of these neologisms (unsurprisingly, most of them have recently been borrowed from English, but there are also quite a few new words composed of previously borrowed stems) and identify various derivational patterns. We also classify words into several large thematic areas, "internet", "marketing", and "multimedia" being among those with the largest number of words. We consider our results preliminary, but believe that, together with the word base collected in the process, they can serve as a starting point in further studies of neologisms and lexical processes that lead to their acceptance into the mainstream language.

Priority areas: IT and mathematics
Language: Russian
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Keywords: социальная сетьсловообразованиеneologismзаимствованиенеологизмsocial networkloan wordnon-vocabularyderivationнесловарное слово
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