ANALYSIS OF SCIENTIFIC ACTIVITIES OF THE DEPARTMENT IN THE CONTEXT OF PRIORITY DIRECTIONS OF RESEARCH AND SCIENTIFIC COOPERATION

UDC 004.048

  • Shuldova Svetlana Georgievna – PhD (Engineering), Associate Professor, Assistant Professor, the Information Technology Software Department. Belarusian State University of Informatics and Radioelectronics (9, Gikalo str., 220005, Minsk, Republic of Belarus). E-mail: shsg@bsuir.by

  • Paramonov Anton Ivanovich – PhD (Engineering), Associate Professor, Head of the Information Systems and Technologies Department. Institute of Information Technology of the Belarusian State University of Informatics and Radioelectronics (28, Kozlova str., 220037, Minsk, Republic of Belarus). E-mail: a.paramonov@bsuir.by

  • Karnaukh Daria Mikhailovna – Master's degree student, Assistant Lecturer, the Information Systems and Technologies Department. Institute of Information Technology of the Belarusian State University of Informatics and Radioelectronics (28, Kozlova str., 220037, Minsk, Republic of Belarus). E-mail: d.karnaukh@bsuir.by

  • Lapitskaya Natalya Vladimirovna – PhD (Engineering), Associate Professor, Head of the Information Technology Software Department. Belarusian State University of Informatics and Radioelectronics (9, Gikalo str., 220005, Minsk, Republic of Belarus). E-mail: lapan@bsuir.by

DOI: https://doi.org/10.52065/2520-6141-2023-266-1-12

Keywords: scientometrics, method, analysis, interaction, co-authorship graph, clustering, modularity, communities.

For citation: Shuldova S. G., Paramonov A. I., Karnaukh D. M., Lapitskaya N. V. Analysis of scientific activities of the department in the context of priority directions of research and scientific cooperation. Proceedings of BSTU, issue 3, Physics and Mathematics. Informatics, 2023, no. 1 (266), pp. 71–76. DOI: https://doi.org/10.52065/2520-6141-2023-266-1-12.

Abstract

The article deals with the methods of scientometric analysis in the context of the tasks of scientometrics to be solved. An approach is proposed for solving the problem of identifying scientific communities and assessing the scientific interaction of employees of a structural subdivision (on the example of the Information Technology Software Department of BSUIR). The problem is formulated and its formal description is given. To test the proposed approach, a data set was obtained from public profiles of Google Academy employees. After pre-processing, including data deduplication and cleaning, a lexical corpus and a term-document matrix are formed, which are converted into an adjacency matrix, on the basis of which a co-authorship graph is built. The main parameters of the graph are considered and the clustering of its vertices is performed. For clustering, a method was used that optimizes the value of modularity. Since modularity depends on the number of transition steps from one vertex to another, a computer experiment was carried out for different values of the parameter. As a result, 11 communities were identified, corresponding to the maximum value of modularity. Some characteristics of communities are analyzed: the percentage of external authors, productivity and citation. Recommendations on the use of information on scientific activities at the department have been developed. Ways for further research are outlined.

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18.01.2023