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  • Саморегуляция фандома: комментарии к публикациям о Шерлоке в тематических группах “ВКонтакте”
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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?

Саморегуляция фандома: комментарии к публикациям о Шерлоке в тематических группах “ВКонтакте”

С. 27–43.
Klimova M.

The study deals with the Sherlock Holmes fandom communicating via specific communities on the social network “VKontakte”. Basing on the broad dynamic notion of the meme as a genre of digital communication as well as on the social and cultural value of in-group memes, comments on the unsuccessful memes were chosen as the object of the research. As for the subject of the research, it constituted the tacit knowledge of the rules of constructing meme samples, the Sherlock Holmes franchise and the rules of the community. The empirical part of the paper consists in the analysis of the negative comments on the memes published in the two most active communities devoted to Sherlock Holmes. The reasons for the audience’s dissatisfaction and the manifestation of “vigilante” identity were revealed and classified. The results testify to the community’s views on the formal structure and content of in-group memes. According to them, a reference to the TV series “Sherlock” essential. In determining such a reference from the audience’s point of view visual allusions are prioritised over verbal and associative ones. Comments on the Sherlock Holmes franchise in terms of following the canon mainly concern the verbal part whereas discussing the fanon is focused on pairings, corresponding to the fanfiction trends. The tendency to idealise both the appearance and personality of Sherlock Holmes in memes is criticised by members of the audience. The implicit rules of the community expressed in the comments testify to the fact that by focusing on the well-known elements of the franchise and rejecting the exaggeration of the fan’s image the analysed fan community is moving towards mainstream.

Language: Russian
Full text
Keywords: комментарииcommentsВконтактеVkontakteШерлок ХолмсfandomфандомSherlock Holmesunsuccessful memesнеудачные мемы

In book

Шерлок Холмс: дедукция и современный мир
Шерлок Холмс: дедукция и современный мир
Fomina E., Морева А. С., Klimova M., Нахман Ф. Г., Khusyainov T., Валяева Н. Ю. М.: Русское общество истории и философии науки, 2021.
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