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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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Синтаксическая позиция «народа» в политическом дискурсе левого и правого популизма (опыт синтаксического анализа на основе NLP)

Филологические науки в МГИМО. 2024. Т. 10. № 2. С. 23–37.
Галочкин А. Е.

This paper attempts to measure populism in English-language speeches of politicians using computational linguistics methods. The relevance of this study is related not only to the rise of populism in the world and the importance of understanding the mechanisms of political discourse, but also to the lack of linguistic research in the context of corpus studies. Most of the methods proposed to date require significant resources or suffer from structural limitations, especially when they rely heavily on the human annotation process to analyze extensive corpus data. The material for the study was public speeches and interviews of right-wing populist politician and 45th President of the United States Donald Trump and political rhetoric of left-wing populist politician Senator Bernie Sanders. The corpus analysis was based on transcripts downloaded from The American Presidency Project and Miller Center websites. The syntactic position of key lexical units is determined using a comprehensive method based on dependency grammar combined with natural language processing (NLP) and van Leeuwen’s linguistic theory. The application of natural language processing methods confirms the assumption that the frequency of politicians’ reference to the people is not the only relevant indicator for measuring people-centrism in (populist) political discourse, as usually proposed in the political science literature. The results of the study indicate that there is no predominant role of the people in the discourse of Trump and Sanders. In most cases, the people appear in a complementary or adjunct position, indicating their secondary importance in their rhetoric. Given that populism implies proximity to the people and is positioned as “vox populi” - “the voice of the people”, it can be assumed that for both Trump and Sanders, addressing the people is only a way to achieve their political goals.

Research target: Philology and Linguistics
Language: Russian
DOI
Text on another site
Keywords: популизмкорпусная лингвистикаpopulismcorpus linguisticsполитический дискурсобработка естественного языкаNatural Language Processing (NLP)political discourcesyntactical parsingсинтаксический парсинг
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