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International Conference on Network Analysis

NET 2018: Network Algorithms, Data Mining, and Applications pp 201–217Cite as

Social Mechanisms of the Subject Area Formation. The Case of “Digital Economy”

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 315))

Abstract

The structure of natural language could be considered a semantic network. This implies the allocation of the speech markers, which describe the subject and semantic areas. In this article, a wide range of texts about the digital economy was analyzed, making it possible to show the thematic structure of this subject area. Central and peripheral concepts were identified to characterize theoretical core concepts and related topics clarifying the application of the digital economy. Identification of the thematic areas was performed in two ways—through the construction of a thematic tree (neural network modeling in the Text Analyst) and the analysis of semantic networks. The results, approaches, and methods of this study could be used during the investigation of the other large thematic fields related to new ideological currents, being developed as an element of social design and management.

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Acknowledgements

The study has been funded by the Russian Academic Excellence Project “5-100”.

Author information

Authors and Affiliations

  1. Higher School of Economics, Moscow, Russian Federation

    Oxana Mikhailova, Galina Gradoselskaya & Alexander Kharlamov

  2. Institute of Higher Nervous Activity and Neurophysiology of RAS, Moscow, Russian Federation

    Alexander Kharlamov

  3. Moscow State Linguistic University, Moscow, Russian Federation

    Alexander Kharlamov

Authors
  1. Oxana Mikhailova
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  2. Galina Gradoselskaya
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  3. Alexander Kharlamov
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Corresponding author

Correspondence to Oxana Mikhailova .

Editor information

Editors and Affiliations

  1. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Ilya Bychkov

  2. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Valery A. Kalyagin

  3. Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  4. Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Oleg Prokopyev

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Mikhailova, O., Gradoselskaya, G., Kharlamov, A. (2020). Social Mechanisms of the Subject Area Formation. The Case of “Digital Economy”. In: Bychkov, I., Kalyagin, V., Pardalos, P., Prokopyev, O. (eds) Network Algorithms, Data Mining, and Applications. NET 2018. Springer Proceedings in Mathematics & Statistics, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-030-37157-9_14

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