• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Book chapter
  • Analyzing Social Networks Services Using FormalConcept Analysis Research Toolbox
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Analyzing Social Networks Services Using FormalConcept Analysis Research Toolbox

Ch. 5. P. 43–54.
Neznanov A., Parinov A.

Nowadays social data analysts use a complicated mix of languages, methods and technologies for analyzing social networks services (SNS) data. In this article we describe approaches and technologies for extracting, analyzing and visualizing social data using Formal Concept Analysis Research Toolbox (FCART). Integrated process of analyzing SNS data with a set of research tools based on Formal Concept Analysis is considered with examples on datasets from Russian segment of LiveJournal.

Language: English
Full text
Text on another site
Keywords: data miningknowledge discoveryFCA (Formal Concept Analysis)applied software systemssocial network analysis
Publication based on the results of:
­­­Data mining based on lattices of closed descriptions and applied ontologies (2015)

In book

CEUR Workshop Proceedings. Proceedings of the International Workshop on Social Network Analysis using Formal Concept Analysis (SNAFCA 2015)
Issue 1534: SNAFCA 2015 Social Network Analysis using Formal Concept Analysis. , Malaga: CEUR Workshop Proceedings, 2015.
Similar publications
Паттерны коллаборации российских социологов: часть 2 – анализ сетей соавторства
Maltseva D., Shcheglova T., Vashchenko V., Социологические исследования 2026 № 1 С. 62–74
The article continues to present the results of the analysis of collaboration networks of Russian sociologists in 2010–2021. It was conducted on the basis of data on co-authorship of scientific articles indexed in the electronic library eLibrary (75,232 scientific publications on sociology). The methodology of bibliometric network analysis implies the construction of several types of ...
Added: May 12, 2026
Recovery degree constrained equiconcept/pseudo-equiconcept reduction in symmetric formal contexts
Junyu B., Fei H., Huilin F. et al., International Journal of Approximate Reasoning 2025 Vol. 187 Article 109541
In Formal Concept Analysis (FCA), concept reduction serves as an important means of simplification. The application scenarios of concept reduction cover various aspects such as data mining, knowledge discovery, strategic decision-making, and rule learning. For symmetric formal contexts, a specialized class of concept reduction exists that can fully recover all knowledge. However, most existing concept ...
Added: December 1, 2025
Formation of Collaboration Networks Among Russian Sociologists (2010–2021)
Maltseva D., Kim A., Semenova A., Operations Research Forum 2025 Vol. 6 Article 89
Due to the non-linear nature of the development of the sociological discipline in the Soviet time, and the existing inequality between central cities and regions in mod- ern Russia, the community of Russian sociologists is characterized by a low level of integration at the local level and selective representation in the international sci- entific community. ...
Added: June 26, 2025
Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected Papers
Springer, 2024.
This book constitutes the refereed proceedings of the 12th International Conference on Analysis of Images, Social Networks and Texts, AIST 2024, held in Bishkek, Kyrgyzstan, during October 17–19, 2024. The 16 full papers included in this book were carefully reviewed and selected from 70 submissions. They were organized in topical sections as follows: Natural Language Processing; Computer Vision; Data Analysis and Machine Learning; ...
Added: May 29, 2025
Clustering with Stable Pattern Concepts
Dudyrev E., Mariia Zueva, Kuznetsov S. et al., , in: FCA4AI 2024: The 12th International Workshop "What can FCA do for Artificial Intelligence?", October 19 2024, Santiago de Compostela, SpainVol. 3911.: CEUR Workshop Proceedings, 2024. P. 47–58.
Clustering aims at finding disjoint groups of similar objects in data and is one major task in Machine Learning. It is also gaining more attention in Formal Concept Analysis community in these last years. This paper proposes an original approach to the clustering of complex data based on Formal Concept Analysis (FCA) and Pattern Structures. ...
Added: April 30, 2025
FCA4AI 2024: The 12th International Workshop "What can FCA do for Artificial Intelligence?", October 19 2024, Santiago de Compostela, Spain
CEUR Workshop Proceedings, 2024.
The eleven preceding editions of the FCA4AI Workshop showed that many researchers working in Articial Intelligence are deeply interested in a well-founded method for classication and data mining such as Formal Concept Analysis (see https://upriss.github.io/fca/fca.html). The FCA4AI Workshop Series started with ECAI 2012 (Montpellier) and the last edition was co-located with IJCAI 2023 (Macao, China). The ...
Added: April 29, 2025
Predicting Student Dropout Through Text and Media Content Analysis of VKontakte Profiles
Gorshkov S., Ignatov D. I., Chernysheva A., IEEE Access 2025 Vol. 13 P. 46732–46746
This paper presents a novel approach to predicting student dropout by analyzing publicly available data from VKontakte social network profiles. Unlike traditional methods that primarily rely on academic and institutional data, our method leverages publicly available content, including photos, videos, music preferences, and textual posts. Image and video content were analyzed using scene recognition models ...
Added: March 20, 2025
Using topic modeling for communities clusterization in the VKontakte social network
Gorshkov S., Ilyushin E., Chernysheva A. et al., International Journal of Open Information Technologies 2021 Vol. 9 No. 5 P. 12–17
Topic modeling is one of the most widely used methods in text analysis. It can be used to select topics as well as to find the topics distributed in each document from the corpus. In this article, we present a method for clustering communities in the social network VKontakte (the most popular Russian social network) ...
Added: December 25, 2024
Citation and bibliographic coupling between authors in the field of social network analysis
Maltseva D., Batagelj V., Journal of Data and Information Science 2024 Vol. 9 No. 4 P. 110–154
Purpose We analyzed the structure of a community of authors working in the field of social network analysis (SNA) based on citation indicators: direct citation and bibliographic coupling metrics. We observed patterns at the micro, meso, and macro levels of analysis. Design/methodology/approach We used bibliometric network analysis, including the “temporal quantities” approach proposed to study temporal networks. Using ...
Added: November 27, 2024
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part X. LNCS, volume 14950
Cham: Springer, 2024.
This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. ...
Added: November 22, 2024
Размежевание или сплочение? Динамика сетевой структуры политических телеграм-каналов: моделирование и эмпирический анализ
Akhremenko A. S., Sinitsina A., Соловьев В. А., Полития: Анализ. Хроника. Прогноз 2024 № 3(114) С. 59–81
In this paper, the authors propose a new methodology to analyze the dynamics of large-scale online network structures caused by significant exogenous shocks (foreign policy crises and the onset of military conflicts). The focus is on diagnosing cohesion or polarization processes. On the first step, mechanisms at the micro-level that may lead to consolidation or ...
Added: September 26, 2024
Loan Portfolio Dataset From MakerDAO Blockchain Project
Chaleenutthawut Y., Davydov V., Evdokimov M. et al., IEEE Access 2024 Vol. 12 P. 24843–24854
Decentralized finance (DeFi) offers a range of financial instruments and services that leverage the capabilities of web3 technology. Maker protocol, which enables users to obtain loans backed by cryptocurrencies, is one of them. Unlike traditional banks, Maker’s data is transparently recorded on the Ethereum blockchain. In this research paper, we focus on analyzing the lending ...
Added: September 4, 2024
2023 IEEE International Conference on Data Mining Workshops (ICDMW) 1–4 December 2023, Shanghai, China
Shanghai: IEEE Computer Society, 2023.
The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, ...
Added: March 20, 2024
Поиск закономерностей и важности признаков в данных виктимизационного опроса
D'yakonov A., Головина А. М., Прикладная математика и информатика 2023 Т. 61 № 74 С. 91–108
A methodology for finding patterns by solving machine learning problems with a teacher is described and applied to the analysis of national victimization survey data. Important features for machine learning models, interesting patterns and inconsistencies in the data are found. Experiments on estimating feature importance using different methods are described. ...
Added: March 18, 2024
Structural Stability of the Russian Sociologists’ Online Community: 2011—2018
Kim A., Maltseva D., Monitoring Obshchestvennogo Mneniya: Ekonomichekie i Sotsial'nye Peremeny 2024 No. 1 P. 202–228
This study deals with an approach to stability evaluation of the community structure on the example of Russian sociologists’ Facebook group. Based on the data from the Facebook group, which consists of 7 years of communication from 2011 till 2018, we constructed the networks based on commenting and reacting. The participants’ activity includes four main ...
Added: December 7, 2023
Сентимент-анализ как метод исследования информационной повестки и общественного мнения (на примере СМИ и социальных сетей КНР)
Анташева М. С., Lobanova P., Isaeva J. K. et al., Социология: методология, методы, математическое моделирование 2023 № 57 С. 7–41
The information agenda broadcast by Chinese media resources is a   source of up-to-date data on public opinion on key issues of social welfare. Due to the technical peculiarities of the organization of Chinese websites and the need to attract additional resources for automatic processing  (parsing)  of texts in Chinese, this topic is not widely represented in domestic and foreign studies. The ...
Added: November 9, 2023
Использование платформы TXM корпусного анализа для анализа текстов сообществ социальных сетей
Fokina A., Chepovskiy A., Chepovskiy A., Вестник Новосибирского государственного университета. Серия: Информационные технологии 2023 Т. 21 № 2 С. 29–38
When forming graphs of interacting objects built when importing data from social networks and instant messaging  networks, text data also act as vertex attributes. In this paper, the authors describe a text research methodology based on corpus analysis procedures. The purpose of this article is to test the methodological tools provided by the TXM software for the ...
Added: October 9, 2023
Constructing decision quivers
Dudyrev E., Kuznetsov S., Napoli A., , in: FCA4AI 2023 What can FCA do for Artificial Intelligence 2023 Proceedings of the 11th International Workshop "What can FCA do for Artificial Intelligence?" co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) Macao, S.A.R. China; August 20, 2023Vol. 3489.: CEUR-WS.org, 2023. P. 69–80.
Rule Learning and Formal Concept Analysis (FCA) are two fields of science that study similar topic yet speak in a very different terms. This paper describes rule-based machine learning models with FCA-based terminology which results in decision quiver model. A decision quiver, discussed in the paper, is a supervised machine learning model that is based ...
Added: October 4, 2023
Description Quivers for Compact Representation of Concept Lattices and Ensembles of Decision Trees
Dudyrev E., Kuznetsov S., Napoli A., , in: 17th International Conference, ICFCA 2023, Kassel, Germany, July 17–21, 2023, Proceedings. Formal Concept Analysis, (LNCS, volume 13934).: Switzerland: Springer, 2023. P. 127–142.
In this paper we introduce and study description quivers as compact representations of concept lattices and respective ensembles of decision trees. Formally, description quivers are directed multigraphs where vertices represent concept intents and (multiple) edges represent generators of intents. We study some properties of description quivers and shed light on their use for describing state-of-the-art symbolic machine ...
Added: October 4, 2023
Патрональная политика и ротация губернаторского корпуса в России: Опыт сетевого анализа
Balandin Y., Gaivoronsky Y., Полития: Анализ. Хроника. Прогноз 2023 № 3(110) С. 67–90
The article is devoted to testing different approaches to explaining the turnover of the heads of the Russian regions after the return of direct gubernatorial elections. Until recently, two basic explanatory models of gubernatorial turnovers — electoral and socio-economic — were the most popular among the Russian political scientists. The influence on such turnovers of ...
Added: September 19, 2023
Data Analysis and Optimization. In Honor of Boris Mirkin's 80th Birthday
Springer, 2023.
This book presents the state-of-the-art in the emerging field of data science and includes models for layered security with applications in the protection of sites—such as large gathering places—through high-stake decision-making tasks. Such tasks include cancer diagnostics, self-driving cars, and others where wrong decisions can possibly have catastrophic consequences. Additionally, this book provides readers with ...
Added: August 31, 2023
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit