Abstract

The goal of the research is to study tools of Data Mining to find latent nature of lexical transformation in annual reports of the state-owned corporation ‘Rosteck’ and to estimate perspectives of extending methodology of businessanalysis by tools of multimodal business-analysis. Identification of trends in vocabulary transformation in annual reports was done by finding indicator features of unique key lexical units and their contexts. The author used methods of multimodal business-analysis and tools of Data Mining to study corporate reports in order to identify the most important signs and trends in business-vocabulary transformation at enterprises and corporations, which is usually ignored by conventional business-analysis. Russian texts of annual reports of ‘Rosteck’ corporation for 2017– 2021 act as initial data for the research. As Data Mining tools the author used Workflow-model on the on-line platform for analysis and data visualization Orange Data Mining 3.3.2. The research showed a clear trend to renewal of the annual report content within the period of analysis. Such units as ‘работник’ (worker), ‘обучение’ (training), ‘платформа’ (platform), ‘трансформация’ (transformation), ‘инициатива’ (initiative) and ‘академия’ (academy) demonstrated maximum dynamics in frequency growth. Context analysis allowed the author to draw a conclusion that transformation in business vocabulary is based on the growing attention of the corporation to problems of digital transformation, development of digital platforms, realization of technological and socio-humanitarian strategic initiatives, raising the quality of workers’ qualification by training in corporate net academy. Implementation of these measures requires upgrading strategy of managing finance, corruption, market and other risks. Multimodal business-analysis is a promising trend in academic research and a tool for resolving applied economic and organizational-managerial problems.

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