Training, Language and Culture (Jun 2021)

Semantic shift in conflict terminology in contemporary Russian socio-cultural media discourse

  • Alina S. Antipova,
  • Maria D. Rabeson,
  • Olga V. Smirnova

DOI
https://doi.org/10.22363/2521-442X-2021-5-2-73-89
Journal volume & issue
Vol. 5, no. 2
pp. 73 – 89

Abstract

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Current socio-cultural means of communication stand no comparison to the ones that existed even a decade ago. Media have introduced new information exchange practices, provided novel areas for communication, triggered wider civic participation in social life worldwide. The increase of digitalised texts available to the public on an everyday basis on the Internet have created media-focused space whose main characteristic is constant content change. Therefore, each specific social sphere may be traced throughout content provided in media sources internationally and locally. Conflict as one of the key ideas of the media zone is not an exception, being one of the most commonly reported topics in the news globally. Our study is based on revealing semantic features of conflict terminology that is understood as the number of related-to-conflict words used together in socio-cultural media discourse. While global contexts are usually more vulnerable to long-lasting meaning change, socially and culturally predetermined local contexts tend to be less considered having shorter time to evolve and be viewed. However, smaller meaning shifts or changes in word usages occur here ubiquitously and may be revealed in short-term perspective of analysing more flexible information slices. The purpose of this study is to reveal contextual short-term meaning changes for conflict terminology in leading federal Russian newspapers and online media sources. The corpus of 10,707 texts was formed based on the occurrence of conflict-related topics as the object of this research. The research period was January-December 2020. The selection and analysis of publications was carried out using Integrum (the information retrieval system for monitoring and analysing the media) and word2vec (an algorithm based on artificial neural networks). The original methodology made it possible to determine the share of publications on conflict in the total mass of media reports to identify key thematic areas of conflict information agenda, features of its geography, to describe the semantic field of conflict and show its dynamics in time.

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