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Network Presentation of Texts and Clustering of Messages

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Internet Science (INSCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11938))

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Abstract

For the purposes of searching for various communities on the Internet, automatic typology of text messages defined via application of methods of cluster analysis may be used. In this paper, we address one of the significant issues in text classification via cluster analysis, namely determination of the number of clusters. For clustering based on semantics, text documents are typically represented in the form of vectors within n-dimensional linear space. What we suggest as a method for determining the number of clusters is the agglomerative clustering of vectors in the linear space. In our work, statistical analysis is combined with neural network algorithms to obtain a more accurate semantic portrait of a text. Then, using the techniques of distributive semantics, mapping of the derived network structures into a vector form is constructed. A statistical criterion for the completion of the clustering process is derived, defined as a Markovian moment. By obtaining automatic partitioning into clusters, one can compare texts that are closest to the centroids with actual content samples or evaluate such texts with the help of experts. If the display of texts in a vector form is adequate, all informational messages from a fixed cluster have the same meaning and the same emotional coloring. In addition, we discuss a possibility to use vector representation of texts for sentiment detection in short texts like search engines input or tweets.

In the part of method assessment, the work is supported by the Presidential grants of the Russian Federation for young Doctors of Science, grant MD-6259.2018.6.

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Acknowledgements

This research in the part of methods evaluation is supported by the Presidential grants of the Russian Federation for young Doctors of Science, grant MD-5962.2018.6.

Author information

Authors and Affiliations

  1. St. Petersburg State University, 7/9, Universitetskaya embankment, St. Petersburg, 199034, Russian Federation

    Andrey V. Orekhov & Svetlana S. Bodrunova

  2. Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, 5A Butlerova Street, Moscow, 117485, Russian Federation

    Alexander A. Kharlamov

  3. Moscow State Linguistic University, 38 Ostozhenka Street, Moscow, 119034, Russian Federation

    Alexander A. Kharlamov

  4. Higher School of Economics, 20 Myasnitskaya Street, Moscow, 101000, Russian Federation

    Alexander A. Kharlamov

Authors
  1. Andrey V. Orekhov
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  2. Alexander A. Kharlamov
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  3. Svetlana S. Bodrunova
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Correspondence to Andrey V. Orekhov .

Editor information

Editors and Affiliations

  1. University of Perpignan Via Domitia, Perpignan Cedex 9, France

    Samira El Yacoubi

  2. University of Florence, Sesto Fiorentino, Italy

    Franco Bagnoli

  3. University of Florence, Sesto Fiorentino, Italy

    Giovanna Pacini

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Orekhov, A.V., Kharlamov, A.A., Bodrunova, S.S. (2019). Network Presentation of Texts and Clustering of Messages. In: El Yacoubi, S., Bagnoli, F., Pacini, G. (eds) Internet Science. INSCI 2019. Lecture Notes in Computer Science(), vol 11938. Springer, Cham. https://doi.org/10.1007/978-3-030-34770-3_18

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  • DOI: https://doi.org/10.1007/978-3-030-34770-3_18

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