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Learning Clusters through Information Diffusion
P. 3151-3157.
Prokhorenkova Liudmila, Tikhonov A., Litvak N.
When information or infectious diseases spread over a network, in many practical cases, one can observe when nodes adopt information or become infected, but the underlying network is hidden. In this paper, we analyze the problem of finding communities of highly interconnected nodes, given only the infection times of nodes. We propose, analyze, and empirically compare several algorithms for this task. The most stable performance, that improves the current state-of-the-art, is obtained by our proposed heuristic approaches, that are agnostic to a particular graph structure and epidemic model.
In book
Vol. WWW ’19: The Web Conference 2019. , NY : Association for Computing Machinery (ACM), 2019
Moroz A., Pashakhin S., Koltsov S., , in : Networks in the Global World V: Proceedings of NetGloW 2020. Lecture Notes in Networks and Systems. Vol. 181.: Springer, 2021. P. 180-195.
Online social networks have become an essential communi- cation channel for the broad and rapid sharing of information. Currently, the mechanics of such information-sharing is captured by the notion of cascades, which are tree-like networks comprised of (re)sharing actions. However, it is still unclear what factors drive cascade growth. Moreover, there is a lack of ...
Added: September 22, 2020
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
Springer, 2021
Volume 1 & 2 Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020 ...
Added: October 31, 2020
Prokhorenkova Liudmila, Tikhonov A., , in : The World Wide Web Conference. Vol. WWW ’19: The Web Conference 2019.: NY : Association for Computing Machinery (ACM), 2019. P. 1498-1508.
Community detection is one of the most important problems in network analysis. Among many algorithms proposed for this task, methods based on statistical inference are of particular interest: they are mathematically sound and were shown to provide partitions of good quality. Statistical inference methods are based on fitting some random graph model (a.k.a. null model) ...
Added: April 21, 2020
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
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
Mirkin B., , in : 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). : Association for Computing Machinery (ACM), 2020. Ch. 05. P. 99-105.
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. We apply the so-called data recovery approach to the problem by combining the least-squares recovery criteria ...
Added: October 31, 2020
Association for Computing Machinery (ACM), 2020
ASONAM '20: International Conference on Advances in Social Networks Analysis and Mining, 7-10 December 2020, The Hague, Netherlands (Virtual). ...
Added: October 31, 2020
Panov M., Ushakov R., Slavnov K., , in : Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications). : Springer, 2018. P. 53-64.
This paper considers the parameter estimation problem in Mixed Membership Stochastic Block Model (MMSB), which is a quite general instance of random graph model allowing for overlapping community structure. We present the new algorithm successive projection overlapping clustering (SPOC) which combines the ideas of spectral clustering and geometric approach for separable non-negative matrix factorization. The proposed algorithm ...
Added: December 7, 2018
Cham : Springer, 2020
21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
Editors
(view affiliations)
Cesar Analide
Paulo Novais
David Camacho
Hujun Yin
Conference proceedings IDEAL 2020 ...
Added: October 31, 2020
Chepovskiy A., Орлов А. О., Вестник Новосибирского государственного университета. Серия: Информационные технологии 2017 Т. 15 № 3 С. 64-73
One of the tasks related to the study of the of complex networks is the task of revealing communities structure – splitting all vertices into groups (communities), so that the vertices of each group are more closely related to each other than to the rest of the graph. A popular algorithm for detecting communities is ...
Added: October 8, 2017
Попов В. А., 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
Соколова Т. В., Chepovskiy A., Системы высокой доступности 2018 Т. 14 № 3 С. 82-86
This paper presents the problem of forming user profiles based ondata from social networks. For user profiling both the user and his friends data are used. Community allocation algorithms in social graphs are used to detect groups of communication. Each community has its own profile, which includes the characteristics of the users that belong to it ...
Added: October 28, 2018
Gayfutdinova N., Kokoreva M. S., Корпоративные финансы 2011 № 3 С. 44-58
The paper presents the results of empirical testing of behavioral capital structure concepts relevance for leverage choice made by Russian companies. Conducted on the sample of 50 large public companies the analysis revealed the insignificance of market timing theory. However the results show that information cascades and management overconfidence and optimism can partly explain the ...
Added: October 2, 2012
Springer, 2021
Added: September 22, 2020
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
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
Дробышевский М., Коршунов А., Turdakov D. Y., Proceedings of the Institute for System Programming of the RAS 2016 Vol. 28 No. 6 P. 153-170
В статье представлены новые алгоритмы расчета модулярности для направленных взвешенных графов с пересекающимися сообществами. Рассматриваются несколько подходов для вычисления модулярности и их расширения. Учитывая вычислительную сложность известных подходов, предлагаются два параллельных расширения, масштабируемых на графы с более 104 вершин. ...
Added: August 28, 2017
Aleskerov F. T., Meshcheryakova N., Сергеева З. В. et al., , in : 2017 IEEE 11th International Conference on Application of Information and Communication Technologies. Vol. 1.: M. : Institute of Electrical and Electoronics Engineers, 2017. P. 48-52.
Trading processes is a vital part of human life and any unstable situation results in the change of living conditions of individuals. We study the power of each country in terms of produce trade. Trade relations between countries are represented as a network, where vertices are territories and edges are export flows. As flows of ...
Added: September 24, 2017
Лещёв Д. А., Сучков Д. В., Хайкова С. П. et al., Вопросы кибербезопасности 2019 Т. 32 № 4 С. 61-71
The purpose of the study: development of methods for analyzing the graph of interacting objects based on the detection of implicit communities in order to solve the problems of searching for the proximity of profiles and the exchange, distribution of information between objects.
Method: importing data from social networks with the subsequent construction of a weighted ...
Added: August 2, 2019
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., , 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