Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus

Research outputpeer-review

2 Citations (Scopus)

Abstract

This paper proposes a linguistically-rich approach to hidden community detection which was tested in experiments with the Russian corpus of VKontakte posts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.
Original languageEnglish
Title of host publicationArtificial Intelligence and Natural Language
Subtitle of host publication9th Conference, AINL 2020, Helsinki, Finland, October 7–9, 2020, Proceedings
EditorsAndrey Filchenkov, Janne Kauttonen, Lidia Pivovarova
Place of PublicationCham
PublisherSpringer Nature
Pages17-33
ISBN (Electronic)978-3-030-59082-6
ISBN (Print)978-3-030-59081-9
DOIs
Publication statusPublished - 30 Sep 2020
Event9th Conference on Artificial Intelligence and Natural Language - Helsinki
Duration: 7 Oct 20209 Oct 2020

Publication series

NameCommunications in Computer and Information Science
Volume1292

Conference

Conference9th Conference on Artificial Intelligence and Natural Language
Abbreviated titleAINL 2020
CountryFinland
CityHelsinki
Period7/10/209/10/20

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