Shalileh S., Social Network Analysis and Mining 2025 Vol. 15212 P. 137–148
Community detection in attributed networks aims to recover clusters in which the within-community nodes are as interconnected and as homogeneous as possible, while the between-communities nodes are as disconnected and as heterogeneous as possible. The current research proposes a straightforward data-driven model with an integrated regularization term to recover communities. For further improvement of the ...
Added: November 30, 2024
Глобина А. К., Глебова С. В., Конфликтология 2020 Т. 15 № 3 С. 127–148
The emerging technologies have penetrated into everyday life and have become natural part of it. Despite the fact that they made the communication, logistics and bureaucracy much simpler, they also originated a group of problems. Questions of incontrollable behaviour of user’s exists in the dialectic symbiosis with fear of total control by government; all of ...
Added: October 26, 2024
Noskov F., Panov M., / Series arXiv "math". 2023.
Community detection is one of the most critical problems in modern network science. Its applications can be found in various fields, from protein modeling to social network analysis. Recently, many papers appeared studying the problem of overlapping community detection, where each node of a network may belong to several communities. In this work, we consider ...
Added: May 31, 2024
Shalileh S., Mirkin B., , in: Complex Networks & Their Applications XII: Proceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023, Volume 2.: Springer, 2024. Ch. 15 P. 185–196.
Added: March 5, 2024
Alina V. Vladimirova, , in: Alternative Paths to Influence: Soft Power and International Politics.: Oxon: Routledge, 2023. Ch. 9 P. 556–571.
Soft power is one of the most influential concepts in the discipline of international relations, yet it is highly criticized for ambiguity and analytical weakness. Thus, through thoughtful literature reviews, scholars continue with clarifying and mapping the theory within a broader political power research programme. It is in this scholarly context that this article offers ...
Added: February 14, 2024
Alina V. Vladimirova, Journal of political power 2022 Vol. 15 No. 3 P. 556–571
Soft power is one of the most influential concepts in the discipline of international relations, yet it is highly criticized for ambiguity and analytical weakness. Thus, through thoughtful literature reviews, scholars continue with clarifying and mapping the theory within a broader political power research programme. It is in this scholarly context that this article offers ...
Added: February 14, 2024
Аванесян Н. Л., Зенькова В. В., Chepovskiy A. et al., Успехи кибернетики 2023 Т. 4 № 2 С. 33–39
In this paper the authors describe the methodology for the statistical analysis of texts in the network of Telegram channels based on comparison of automatically generated frequency dictionaries by methods of correlation analysis. Coefficients of pairwise rank correlation are considered for comparing the frequency characteristics of texts in natural language. The method is proposed to ...
Added: July 19, 2023
Chepovskiy A., Успехи кибернетики 2023 Т. 4 № 1 С. 56–64
The paper considers the problems of analyzing graphs that represent complex networks of interacting objects. The relevant domains are described, social network graph analysis and implicit community detection are considered. The key graph-based community detection algorithms and the quality assessment of their results are discussed. The author proposed promising development trends using the graphs representing actual social ...
Added: March 31, 2023
Chepovskiy A., , in: The 6th International Conference on Complex Networks and Their Applications. Nov. 29 - Dec. 01, 2017, Lyon (France), Book of abstracts. ISBN 978-2-9557050-2-5.: Springer, 2017. P. 336–340.
One of the tasks related to the study of the of complex networks is the problem of revealing communities structure. Algorithms to split all vertices into groups, named communities, so that the vertices of each group are more closely related to each other than to the rest of the graph are widely investigated nowadays. This is so-called ...
Added: March 22, 2023
Chepovskiy A., Вопросы кибербезопасности 2023 № 1(53) С. 75–81
The purpose of the study: search for a technique for constructing and analyzing a graph of interacting objects in the network of Telegram channels, including the calculation of psycholinguistic characteristics of texts. This technique makes it possible to classify groups of channels and evaluate their informational impact on users.
Method: (U, M, R)-model is used to build a weighted ...
Added: March 6, 2023
Chepovskiy A., М.: Национальный открытый университет «ИНТУИТ», 2022.
В монографии рассмотрены различные математические модели для решения задач анализа сетей взаимодействующих объектов систем телекоммуникаций. Предназначена для разработчиков информационных систем, специалистов в области анализа данных. ...
Added: November 18, 2022
Popov V., Chepovskiy A., Труды Института системного анализа Российской академии наук 2022 Т. 72 № 4 С. 39–50
In this paper, the authors present the “Galaxies method” to reveal implicit communities on the
graph of interacting objects obtained by importing a network of channels from the Telegram messenger. This
method is based on successive identification of overlapping communities on the initial weighted graph, further
construction of a new graph, in which the vertices are the communities ...
Added: October 30, 2022
Popov V., Chepovskiy A., Вестник Новосибирского государственного университета. Серия: Информационные технологии 2022 Т. 20 № 2 С. 60–71
In this paper, an algorithm to import data from the messenger Telegram and to build weighted graphs of interacting objects is described. To import data, the given Telegram-channels are taken as a basis. Then, iteractively channels that had any of the recorded three interactions with previous ones are revealed: common external links, mentions of each ...
Added: September 2, 2022
Makarov I., Oborevich A., , in: Proceedings of IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI'21), 18-20 Nov. 2021.: NY: IEEE, 2021. P. 000127–000130.
Graph visualization is an effective and efficient way to discover complex inter-connections between elements within the nested structure of data. To accomplish this type of representation machine learning algorithms use a technique called graph embedding and node embedding in particular. However, in this paper, we will compare well-known techniques to yet largely under-explored setting of ...
Added: January 19, 2022
Popov V., Chepovskiy A., Вестник Новосибирского государственного университета. Серия: Информационные технологии 2021 Т. 19 № 2 С. 76–91
In this paper, the authors describe an algorithm for importing data from the social network Twitter and building weighted social graphs. To import data, the given posts are taken as a basis, users who have had any of the recorded interactions with them are downloaded. Further, the algorithm focuses on the given configuration and uses ...
Added: July 25, 2021
Makarov I., Makarov M., Kiselev D., PeerJ Computer Science 2021 Vol. 7 Article e526
Today, increased attention is drawn towards network representation learning, a technique that maps nodes of a network into vectors of a low-dimensional embedding space. A network embedding constructed this way aims to preserve nodes similarity and other specific network properties. Embedding vectors can later be used for downstream machine learning problems, such as node classification, ...
Added: March 31, 2021
Chepovskiy A., Leshchev D. A., Khaykova S.P., , in: Complex Networks & Their Applications IX. Volume 1: Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020.: Springer, 2021. P. 38–50.
The processing of networks of interacting objects makes it possible to solve topical issues in the modern world of identifying opinion leaders and channels for the dissemination and exchange of information. In this work, the structure of networks of interacting objects and their possible analysis with the help of weighted graphs based on the interaction ...
Added: January 6, 2021