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Kravets A.V. [Content analysis of the publication orientation of the journal «Sociological Research for 2020–2023 years»] World of Science. Series: Sociology, Philology, Cultural Studies, 2023, Vol. 14, No. 2. Available at: https://sfk-mn.ru/PDF/39SCSK223.pdf (in Russian).

Content analysis of the publication orientation of the journal «Sociological Research for 2020–2023 years»

Kravets Alexandr Vitalevich
Novosibirsk State University of Economics and Management, Novosibirsk, Russia
E-mail: apt-words@mail.ru
ORCID: https://orcid.org/0000-0003-4694-0973
RSCI: https://www.elibrary.ru/author_profile.asp?id=355106

Abstract. In this article, the author presents the results of the content analysis of scientific publications of the journal Sociological Research for the period from 2020 to 2023. The content analysis of scientific texts was carried out as follows. Collection of articles of the journal of Sociological Research for the period of selected publications for 2020–2023 and saving files of articles in text format. With the help of the Lecta software, the text files were divided into fragments, and a dictionary was created — the so-called categorical grid of texts. On the basis of the dictionary, semantic chains of lexemes were created that relate to a single problem. The unit of account was a token, and the unit of analysis was fragments of scientific articles published in the journal of Sociological Research for the previously specified period. The criterion for the informativeness of the model was the ratio of the size of the created dictionary to the total number of words of the source text (the created dictionary, taking into account the combination of words into lexemes, should be approximately 30 % of the number of words in the analyzed text). The resulting and optimized text model was subjected to factor analysis. In the course of factor analysis, factor loads were calculated based on the obtained frequency matrix, the interpretation of the matrix of factor loads and the allocation of the main topics, the calculation of the coordinates of text fragments in the space of the obtained factors. In the course of nonparametric scaling of latent factors based on their calculated regression coefficients, groups of the closest latent factors, and in fact scientific topics that are covered in publications in the journal Sociological Research for the period from 2020 to 2023, were obtained based on the results of factor analysis. The result of the analysis was the definition and interpretation of the main topics, the analysis of the plot structure of scientific texts as a whole.

Keywords: methodology; methods; content analysis; publications; frequency; unit of analysis; factors; scaling; topics

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