Three-step Algorithms for Detection of High Degree Nodes in Online Social Networks

Shaikhelislamov D.; Drobyshevskiy M.; D. Y. Turdakov; Yatskov A.; Varlamov M.; Aivazov D.

doi:10.1109/IVMEM51402.2020.00014

АБВ
АБВ
АБВ

Обычная версия сайта

Priority areas

by year

Subject

News

July 24, 2026

‘I Like Self-Fulfilling Prophecies

Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.

July 24, 2026

'Physics Is What the World Is Literally Built On'

Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.

July 20, 2026

Scientists Create Open Dataset for Studying Concentration

A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications

?

Three-step Algorithms for Detection of High Degree Nodes in Online Social Networks

Ch. 9. P. 43–48.

Shaikhelislamov D., Drobyshevskiy M., Turdakov D. Y., Yatskov A., Varlamov M., Aivazov D.

Language: English

DOI

Keywords: Network crawling network sampling node influence

In book

Proceedings of the 2020 Ivannikov Memorial Workshop

Los Alamitos: IEEE Communications Society, 2020.

Graph Neural Network for Crawling Target Nodes in Social Networks

Danil Shaikhelislamov, Denis Turdakov, , in: 2022 Ivannikov Ispras Open Conference (ISPRAS).: IEEE, 2022. P. 31–36.

Social networks crawling is in the focus of active research the last years. One of the challenging task is to collect target nodes in an initially unknown graph given a budget of crawling steps. Predicting a node property based on its partially known neighbourhood is at the heart of a successful crawler. In this paper ...

Added: February 3, 2025

Collecting Influencers: A Comparative Study of Online Network Crawlers

Drobyshevskiy M., Aivazov D., Turdakov D. Y. et al., , in: Proceeding 2019 Ivannikov Ispras Open Conference (ISPRAS).: IEEE Computer Society, 2019. P. 42–48.

Added: October 12, 2021