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Methodological Foundations of Qualitative and Quantitative Analysis of IT Companies' Work in Social Networks

https://doi.org/10.35596/1729-7648-2025-31-2-5-12

Abstract

The article considers the methodological principles of qualitative and quantitative analysis of SMM activities of IT companies. The goals and objectives of such analysis are formulated, and the company՚s activity indicators in social networks are highlighted. A consistent comparison of the uniqueness of Facebook posts with X, LinkedIn with X and Facebook is carried out, and company posts in social networks are grouped into categories depending on the main topic. Along with topics, it is proposed to evaluate other characteristics of posts that allow exploring the breadth of SMM tools: post features, style, color scheme, hashtags, links. It is proposed to evaluate the involvement of the subscribers of the company and social network users through the number of likes, as well as through the total number of reposts and comments for each post. To systematize the final results of the research, a form for analyzing the work of companies in social networks was created.

About the Authors

M. P. Batura
Belarusian State University of Informatics and Radioelectronics
Russian Federation

Dr. Sci. (Tech.), Professor, Head of the R&D Laboratory “New Educational Technologies” 

Minsk 



I. V. Marakhina
Belarusian State University of Informatics and Radioelectronics
Russian Federation

Маrakhina Ina Victorovna, Cand. Sci. (Econ.), Associate Professor, Associate Professor at the Economics Department  

220005, Minsk, Platonova St., 39–809 



U. A. Parkhimenko
Belarusian State University of Informatics and Radioelectronics
Belarus

Cand. Sci. (Econ.), Associate Professor, Head of the Economics Department 

Minsk



References

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Review

For citations:


Batura M.P., Marakhina I.V., Parkhimenko U.A. Methodological Foundations of Qualitative and Quantitative Analysis of IT Companies' Work in Social Networks. Digital Transformation. 2025;31(2):5-12. (In Russ.) https://doi.org/10.35596/1729-7648-2025-31-2-5-12

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ISSN 2522-9613 (Print)
ISSN 2524-2822 (Online)