innovationИнформация и инновацииInformation and Innovations1994-24432949-2157МЦНТИ10.31432/1994-2443-2024-19-3-46-79innovation-275Research ArticleНАУКОМЕТРИЯ И БИБЛИОМЕТРИЯSCIENTOMETRICS AND BIBLIOMETRICSПроверочная методология выявления актуальных научных вопросов в новых публикациях, цитирование которых еще не установленоA proof-of-concept methodology for identifying topical scientific issues in new publications whose citations have not yet been establishedhttps://orcid.org/0000-0001-9903-2800ЧигаревБ. Н.ChigarevB. N.

Борис Николаевич Чигарев, к. ф.- м. н., ведущий инженер по научно-технической информации

г. Москва

Boris N. Chigarev, Cand. Sci. (Phys.-Math.), Leading Engineer on Scientific and Technical Information

Moscow

bchigarev@ipng.ruИнститут проблем нефти и газа Российской академии наукРоссияOil and Gas Research Institute, Russian Academy of SciencesRussian Federation2024240120251934679Copyright © Чигарев Б.Н., 20252025Чигарев Б.Н.Chigarev B.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://journal.icsti.int/jour/article/view/275

Выявление актуальных исследовательских проблем с использованием библиометрических данных осложняется тем, что цитирование публикаций последних лет еще не сформировано. В данной работе предлагается использовать для оценки веса ключевого слова, встречающегося в рассматриваемой выборке, не цитирование статьи, а среднюю цитируемость журнала за два года. Для выявления терминов, характеризующих релевантные исследовательские темы, предлагается представить сеть совместной встречаемости терминов в координатах средней встречаемости термина в год и средней нормализованной цитируемости термина для визуализации графика. Кроме того, данная методология предполагает использование предварительной обработки ключевых слов с использованием словаря лемматизации. Для анализа были использованы 3696 библиометрических записей за 2022–2024 гг. с платформы ScienceDirect по теме цифровизации промышленности. Последовательно использовались программы VOSviewer и Scimago Graphica. Первый использовался для отображения общего ландшафта исследования, а второй — для более детального анализа отдельных срезов библиометрических данных, полученных с помощью VOSviewer. «Выпуклая оболочка» использовалась для облегчения восприятия границ кластеров. После анализа данных и выделения терминов предлагается предоставить контекст, цитируя строки из публикаций и определяя менее известные термины. Цифровизация отрасли — это не только техническая и технологическая проблема, но и экономическая, о чем свидетельствуют такие термины, как «цифровая экономика» и «Индустрия 5.0».

Identification of topical research issues using bibliometric data is complicated by the fact that the citation of publications from recent years has not yet been formed. In this paper, it is proposed to use the average citation of the journal over two years rather than the article citation to estimate to estimate the weight of the keyword occurring in the sample under consideration. In order to identify the terms that characterize relevant research topics, it is proposed to represent the term co-occurrence network in coordinates of the average occurrence of the term per year and the average normalized citation of the term to visualize the graph. Furthermore, this methodology proposes the use of preprocessing of keywords using a lemmatization dictionary. 3,696 bibliometric records for 2022–2024 from the ScienceDirect platform on the topic of industry digitalization were used for the analysis. The VOSviewer and Scimago Graphica programs were used sequentially. The former was used to display the overall landscape of the study, while the latter was used to analyze in more detail the individual slices of bibliometric data obtained with VOSviewer. A ‘convex hull’ was used to facilitate the perception of cluster boundaries. After analysing the data and highlighting the terms, it is proposed to provide context by quoting strings from publications and defining of lesser-known terms. The industry digitalization is not only a technical and technological issue but also an economic one, as evidenced by terms such as ‘digital economy’ and ‘Industry 5.0’.

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The authors declare that there are no conflicts of interest present.