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Using Machine Linguistics to Analyze Trade and Economic News

Author

Listed:
  • Andrey Nikolaevich SPARTAK

    (Russian Market Research Institute, Moscow, Russia
    Russian Foreign Trade Academy, Moscow, Russia)

  • Ivan Nikolaevich OLEYNIKOV

    (Russian Foreign Trade Academy, Moscow, Russia)

  • Alexander Alekseevich SHATILOV

    (Russian Foreign Trade Academy, Moscow, Russia)

  • Fedor Mikhailovich YARONSKIY

    (Russian Foreign Trade Academy, Moscow, Russia)

Abstract

Monitoring international trade and economic news, selecting the relevant ones and quickly analyzing the current state of the world economy is an important activity of economic departments. However, it is practically impossible to manually collect the necessary articles from a huge number of online sources, to visually check and then categorize them. The purpose of this paper is to show the stages of collection, preparation of news texts for processing, markup and further classification of trade and economic news using machine linguistics models, to describe which soft ware tools and modeling approaches were used in the paper, and to demonstrate the results practical application of the built system.

Suggested Citation

  • Andrey Nikolaevich SPARTAK & Ivan Nikolaevich OLEYNIKOV & Alexander Alekseevich SHATILOV & Fedor Mikhailovich YARONSKIY, 2022. "Using Machine Linguistics to Analyze Trade and Economic News," Russian Foreign Economic Journal, Russian Foreign Trade Academy Ministry of economic development of the Russian Federation, issue 12, pages 55-67, December.
    • Handle: RePEc:alq:rufejo:rfej_2022_12_55-67
    DOI: 10.24412/2072-8042-2022-12-55-67
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