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

Conference paper
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Part of the Communications in Computer and Information Science book series (CCIS, volume 1292)

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.

Keywords

Hidden communities Corpus linguistics Social networks Author-topic models Automatic topic labeling 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Saint Petersburg State UniversitySaint PetersburgRussia

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