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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">scieditor</journal-id><journal-title-group><journal-title xml:lang="en">Science Editor and Publisher</journal-title><trans-title-group xml:lang="ru"><trans-title>Научный редактор и издатель</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2542-0267</issn><issn pub-type="epub">2541-8122</issn><publisher><publisher-name>АНРИ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.24069/SEP-251041</article-id><article-id custom-type="elpub" pub-id-type="custom">scieditor-467</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>SCIENTIFIC COMMUNICATIONS</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>НАУЧНЫЕ КОММУНИКАЦИИ</subject></subj-group></article-categories><title-group><article-title>Author keywords and editorial terms in the abstract database: a statistical analysis of differences</article-title><trans-title-group xml:lang="ru"><trans-title>Авторские ключевые слова и редакторские термины в реферативной базе данных: статистический анализ различий</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0005-5149-5669</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Федорец</surname><given-names>Олег Владимирович</given-names></name><name name-style="western" xml:lang="en"><surname>Fedorets</surname><given-names>Oleg V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат технических наук, заведующий лабораторией средств автоматизации ВИНИТИ РАН, SPIN-код: 3254-1900</p></bio><bio xml:lang="en"><p>Cand. Sci. (Eng.), Head of Automation Tools Laboratory</p></bio><email xlink:type="simple">ovfs@bk.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3288-3755</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Солошенко</surname><given-names>Наталия Сергеевна</given-names></name><name name-style="western" xml:lang="en"><surname>Soloshenko</surname><given-names>Nataliya S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>кандидат педагогических наук, заведующий отделом комплектования ВИНИТИ РАН</p></bio><bio xml:lang="en"><p>Cand. Sci. (Educ.), Head of the Acquisitions Department</p></bio><email xlink:type="simple">solns@viniti.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Всероссийский институт научной и технической информации Российской академии наук (ВИНИТИ РАН)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>All-Russian Institute for Scientific and Technical Information, Russian Academy of Sciences (VINITI RAS)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>14</day><month>02</month><year>2026</year></pub-date><volume>10</volume><issue>2</issue><fpage>223</fpage><lpage>240</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Fedorets O.V., Soloshenko N.S., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Федорец О.В., Солошенко Н.С.</copyright-holder><copyright-holder xml:lang="en">Fedorets O.V., Soloshenko N.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.scieditor.ru/jour/article/view/467">https://www.scieditor.ru/jour/article/view/467</self-uri><abstract><p>Author keywords, unlike terms assigned by professional indexers, are not regulated by normative documents or controlled by special dictionaries. The aim of this study is to identify statistical differences between two sets of keywords (KWs): those assigned by authors, on the one hand, and those assigned by editors of abstract database of VINITI RAS, on the other. It is believed that confirming and understanding these differences may be useful for more rational use of keywords obtained from various sources. A comparative analysis of quantitative indicators of the novelty and lexical diversity of author and editorial KWs was conducted for the first time in this study. A comparison of the inclusion measures of author and editorial KWs in other metadata elements was conducted for the first time on several independent thematic samples. The methodological basis of the study is generalization—the identification and quantitative analysis of common features inherent in the studied data arrays. The empirical base of the study consisted of five independent statistical samples, the size of which varied from 10.40 thousand to 18.97 thousand articles. The topics of the samples corresponded to five headings of the State Rubricator of Scientific and Technical Information: 52. Mining; 53. Metallurgy; 55. Mechanical Engineering; 61. Chemical Technology. Chemical Industry; 73. Transport. We selected Russian-language articles uploaded to the VINITI abstract database in 2021–2024 and simultaneously containing the following non-empty metadata elements: title, author’s keywords, author’s abstract, editor’s keywords, and an abstract specially prepared for the VINITI abstract database. For each sample and separately for author’s and editor’s KWs, point statistical estimates of the identified common features were obtained: lexical diversity, novelty, and inclusion of keywords in other metadata elements (title and abstract). Similar statistical differences of author’s and editor’s KWs were observed across all five thematic collections: the degree of lexical diversity in author-generated KWs is higher than that of editor-generated terms; the novelty coefficient of author-generated KWs is higher than that of editor-generated terms; the novelty coefficient of author-generated annotations is higher than that of abstracts; and the degree of inclusion of author-generated KWs in article titles is lower than the degree of inclusion of editor-generated terms. Replication of the identified differences across five independent thematic samples, corresponding to randomly selected fields of knowledge, suggests the statistical stability of these differences. The vocabulary of author KWs is more variable over time compared to the more stable vocabulary of editor-generated terms, which may be useful for the rapid identification of new terminology and scientific frontiers. Unlike editor-generated KWs, author-generated KWs cannot independently express the main themes and concepts of a document, as they supplement the terms that can be extracted from publication titles.</p></abstract><trans-abstract xml:lang="ru"><p>Авторские ключевые слова (КС), в отличие от терминов, присвоенных профессиональными индексаторами, не регулируются нормативными документами и не контролируются с помощью специальных словарей. Цель исследования — выявление статистических различий между массивами КС: присвоенных авторами, с одной стороны, и редакторами реферативной базы данных Всероссийского института научной и технической информации (ВИНИТИ) — с другой. Предполагается, что подтверждение и понимание этих различий может оказаться полезным для более рационального использования КС, полученных из различных источников, в поисковых системах и при библиометрических исследованиях. Впервые выполнен сравнительный анализ количественных показателей новизны и лексического разнообразия авторских и редакторских КС, а также сравнение мер включения авторских и редакторских КС в другие элементы метаданных на нескольких независимых тематических выборках. Методологической основой исследования является обобщение — выделение и количественный анализ общих признаков, присущих изучаемым массивам данных. Эмпирическую базу исследования составили пять независимых статистических выборок объемом от 10,40 до 18,97 тыс. статей. Тематика выборок соответствовала пяти рубрикам Государственного рубрикатора научно-технической информации (ГРНТИ): «52. Горное дело; 53. Металлургия; 55. Машиностроение; 61. Химическая технология. Химическая промышленность; 73. Транспорт». Отбирались русскоязычные статьи, загруженные в реферативную базу данных ВИНИТИ в 2021–2024 гг. и одновременно имеющие следующие непустые элементы метаданных: заглавие, авторские КС, авторскую аннотацию, редакторские КС и реферат, специально подготовленный для этой базы данных. Для каждой выборки и по отдельности для авторских и редакторских КС были получены точечные статистические оценки выделенных общих признаков: лексического разнообразия, новизны и включенности КС в другие элементы метаданных. Во всех пяти тематических коллекциях наблюдались одинаковые статистические различия авторских и редакторских КС: мера лексического разнообразия авторских КС выше, чем редакторских; коэффициент новизны у авторских КС выше, чем у редакторских КС, а у авторских аннотаций выше, чем у рефератов; мера включения авторских КС в заглавие статьи ниже, по сравнению с аналогичным показателем для редакторских терминов. Повторение выявленных различий в пяти независимых тематических выборках, соответствующих случайно выбранным областям знаний, позволяет говорить о статистической устойчивости этих различий. Лексика авторских КС более изменчива во времени по сравнению с более стабильной лексикой редакторских КС, что может быть полезно для оперативного выявления новой терминологии и фронтиров науки. В отличие от редакторских, авторские КС не могут самостоятельно выражать основные темы и понятия документа, так как являются дополнением к терминам, которые можно извлечь из заглавий публикаций. </p></trans-abstract><kwd-group xml:lang="ru"><kwd>научные журналы</kwd><kwd>авторские ключевые слова</kwd><kwd>реферативная база данных</kwd><kwd>редакторские термины</kwd><kwd>тематические коллекции статей</kwd><kwd>мешок слов</kwd><kwd>стемминг</kwd><kwd>сравнительный статистический анализ</kwd><kwd>мера включения</kwd><kwd>лексическое разнообразие</kwd><kwd>коэффициент новизны</kwd></kwd-group><kwd-group xml:lang="en"><kwd>scientific journals</kwd><kwd>author keywords</kwd><kwd>abstract database</kwd><kwd>editor’s keywords</kwd><kwd>thematic collections of articles</kwd><kwd>bag of words</kwd><kwd>stemming</kwd><kwd>comparative statistical analysis</kwd><kwd>inclusion measure</kwd><kwd>lexical diversity</kwd><kwd>novelty coefficient</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Работа выполнена в рамках государственного задания ВИНИТИ РАН по теме № FFFU-2025-0009 «Аналитические исследования динамики трансформации предметных профилей сериальных изданий по приоритетным направлениям науки, техники и технологий».</funding-statement><funding-statement xml:lang="en">The work was performed within the framework of the VINITI RAS state assignment on topic No. FFFU-2025-0009 “Analytical studies of the dynamics of transformation of subject profiles of serial publications in priority areas of science, technology and technology”.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Singh P., Singh V.K., Kanaujia A. Exploring the publication metadata fields in Web of Science, Scopus and Dimensions: Possibilities and ease of doing scientometric analysis. Journal of Scientometric Research. 2024;13(3):715-731. https://doi.org/10.5530/jscires.20041144</mixed-citation><mixed-citation xml:lang="en">Chen Y. N., Ke H. R. A study on mental models of taggers and experts for article indexing based on analysis of keyword usage. Journal of the Association for Information Science and Technology. 2014; 65(8): 1675-1694.  https://doi.org/10.1002/asi.23077</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Stapleton S.C., Dinsmore C.S., Van Kleec D., Ma X. Computer-assisted indexing complements manual selection of subject terms for metadata in specialized collections. College &amp; Research Libraries. 2021;82(6):792-807. https://doi.org/10.5860/crl.82.6.792</mixed-citation><mixed-citation xml:lang="en">Cobo M. J., López-Herrera A. G., Herrera-Viedma E., Herrera F. An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of informetrics. 2011; 5(1): 146-166. https://doi.org/10.1016/j.joi.2010.10.002</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Gbur E.E., Trumbo B.E. Key words and phrases – the key to scholarly visibility and efficiency in an information explosion. The American Statistician. 1995;49(1):29-33. https://doi.org/10.1080/00031305.1995.10476108</mixed-citation><mixed-citation xml:lang="en">Gbur, E. E., &amp; Trumbo, B. E. Key Words and Phrases — The Key to Scholarly Visibility and Efficiency in an Information Explosion. The American Statistician, 1995; 49(1), 29–33. https://doi.org/10.1080/00031305.1995.10476108</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Uddin S., Khan A. The impact of author-selected keywords on citation counts. Journal of Informetrics. 2016;10(4):1166-1177. https://doi.org/10.1016/j.joi.2016.10.004</mixed-citation><mixed-citation xml:lang="en">Gil-Leiva I., Alonso-Arroyo A. Keywords given by authors of scientific articles in database descriptors. Journal of the American society for information science and technology. 2007; 58(8): 1175-1187. https://doi.org/10.1002/asi.20595</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Peset F., Garzón-Farinós F., González L.M., et al. Survival analysis of author keywords: An application to the library and information sciences area. Journal of the Association for Information Science and Technology. 2020;71(4):462-473. https://doi.org/10.1002/asi.24248</mixed-citation><mixed-citation xml:lang="en">Golub, K. Automated Subject Indexing: An Overview. Cataloging &amp; Classification Quarterly, 2021; 59(8), 702–719. https://doi.org/10.1080/01639374.2021.2012311</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Hjørland B. Indexing: Concepts and theory. Knowledge Organization. 2018;45(7):609-639. https://doi.org/10.5771/0943-7444-2018-7-609</mixed-citation><mixed-citation xml:lang="en">González, L. M., García-Massó, X., Pardo-Ibañez, A., Peset, F., &amp; Devís-Devís, J. An author keyword analysis for mapping Sport Sciences. PloS one, 2018; 13(8), e0201435. https://doi.org/10.1371/journal.pone.0201435</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Golub K. Automated subject indexing: An overview. Cataloging &amp; Classification Quarterly. 2021;59(8):702-719. https://doi.org/10.1080/01639374.2021.2012311</mixed-citation><mixed-citation xml:lang="en">Hjørland, B. Indexing: Concepts and Theory. KNOWLEDGE ORGANIZATION, 2018; 45(7), 609–639. https://doi.org/10.5771/0943-7444-2018-7-609</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Tripathi M., Kumar S., Sonker S.K., Babbar P. Occurrence of author keywords and keywords plus in social sciences and humanities research: A preliminary study. COLLNET Journal of Scientometrics and Information Management. 2018;12(2):215-232. https://doi.org/10.1080/09737766.2018.1436951</mixed-citation><mixed-citation xml:lang="en">Lu W., Li X., Liu Z., Cheng Q. How do author-selected keywords function semantically in scientific manuscripts? Knowledge Organization: KO. 2019; 46(6): 403.  https://doi.org/10.5771/0943-7444-2019-6-403</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Cobo M.J., López-Herrera A.G., Herrera-Viedma E., Herrera F. An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics. 2011;5(1):146-166. https://doi.org/10.1016/j.joi.2010.10.002</mixed-citation><mixed-citation xml:lang="en">Lu W., Liu Z., Huang Y., Bu Y., Li X., Cheng Q. How do authors select keywords? A preliminary study of author keyword selection behavior. Journal of Informetrics. 2020; 14(4): 101066. https://doi.org/10.1016/j.joi.2020.101066</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Wei R.-Z., Liu X.-Y., Lyu P.-H. Bibliometrics of public administration research hotspots: Topic keywords, author keywords, keywords plus analysis. Heliyon. 2024;10(21):e39352. https://doi.org/10.1016/j.heliyon.2024.e39352</mixed-citation><mixed-citation xml:lang="en">Lu, W., Huang, S., Yang, J., Bu, Y., Cheng, Q., &amp; Huang, Y. Detecting research topic trends by author-defined keyword frequency. Information Processing &amp; Management, 2021; 58(4), 102594. https://doi.org/10.1016/j.ipm.2021.102594</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Chen Y.-N., Ke H.-R. A study on mental models of taggers and experts for article indexing based on analysis of keyword usage. Journal of the Association for Information Science and Technology. 2014;65(8):1675-1694. https://doi.org/10.1002/asi.23077</mixed-citation><mixed-citation xml:lang="en">Malvern, D., Richards, B., Chipere, N., &amp; Durán, P. Lexical Diversity and Language Development (3), 2004; Palgrave Macmillan UK; https://doi.org/10.1057/9780230511804</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Lu W., Li X., Liu Z., Cheng Q. How do author-selected keywords function semantically in scientific manuscripts? Knowledge Organization. 2019;46(6):403-418. https://doi.org/10.5771/0943-7444-2019-6-402</mixed-citation><mixed-citation xml:lang="en">McCarthy, P. M., &amp; Jarvis, S. MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods, 2010; 42(2), 381–392. https://doi.org/10.3758/BRM.42.2.381</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Lu W., Liu Z., Huang Y., et al. How do authors select keywords? A preliminary study of author keyword selection behavior. Journal of Informetrics. 2020;14(4):101066. https://doi.org/10.1016/j.joi.2020.101066</mixed-citation><mixed-citation xml:lang="en">Nabilah, N., Zafrullah, Z., Nakamo, S. J., &amp; Mwakapemba, M. L. Mapping the Evolution of Research Themes on ChatGPT Integration in Education: Thematic and Novelty Keywords. Elementaria: Journal of Educational Research, 2025; 3(1), 34–44. https://doi.org/10.61166/elm.v3i1.90</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Дубинина Е.Ю. Выделение ключевых слов текста научной статьи в процессе создания автоматического реферата. Вестник Воронежского государственного университета. Серия: Филология. Журналистика. 2020;(1):26-28. URL: http://www.vestnik.vsu.ru/pdf/phylolog/2020/01/2020-01-06.pdf</mixed-citation><mixed-citation xml:lang="en">Pearson, W. S. Research Topics in Applied Linguistics as Keywords from Authors and Keywords from Abstracts: A Bibliometric Study. In A Scientometrics Research Perspective in Applied Linguistics. 2024; pp. 113-134. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-51726-6_5</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Dubinina E.Yu. Selection of keywords in a scientific article in the process of creating an automatic abstract. Proceedings of Voronezh State University. Series: Philology. Journalism. 2020;(1):26-28. (In Russ.). URL: http://www.vestnik.vsu.ru/pdf/phylolog/2020/01/2020-01-06.pdf</mixed-citation><mixed-citation xml:lang="en">Peset, F., Garzón‐Farinós, F., González, L., García‐Massó, X., Ferrer‐Sapena, A., Toca‐Herrera, J., &amp; Sánchez‐Pérez, E. Survival analysis of author keywords: An application to the library and information sciences area. Journal of the Association for Information Science and Technology, 2020; 71(4), 462–473. https://doi.org/10.1002/asi.24248</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Yang J., Liu Z., Cheng X., Ye G. Understanding the keyword adoption behavior patterns of researchers from a functional structure perspective. Scientometrics. 2024;129(6):3359-3384. https://doi.org/10.1007/s11192-024-05031-1</mixed-citation><mixed-citation xml:lang="en">Powell, J., Klein, M., &amp; Balakireva, L. Combining keyphrase extraction and lexical diversity to characterize ideas in publication titles (3; Version 1). arXiv, 2022; https://doi.org/10.48550/ARXIV.2208.13978</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Gil-Leiva I., Alonso-Arroyo A. Keywords given by authors of scientific articles in database descriptors. Journal of the American Society for Information Science and Technology. 2007;58(8):1175-1187. https://doi.org/10.1002/asi.20595</mixed-citation><mixed-citation xml:lang="en">Singh, P., Singh, V. K., &amp; Kanaujia, A. Exploring the Publication Metadata Fields in Web of Science, Scopus and Dimensions: Possibilities and Ease of doing Scientometric Analysis. Journal of Scientometric Research, 2024; 13(3), 715–731. https://doi.org/10.5530/jscires.20041144</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang J., Yu Q., Zheng F., et al. Comparing keywords plus of WOS and author keywords: A case study of patient adherence research. Journal of the Association for Information Science and Technology. 2016;67(4):967-972. https://doi.org/10.1002/asi.23437</mixed-citation><mixed-citation xml:lang="en">Song, C., Chen, K., Jin, Y., Chen, L., &amp; Huang, Z. Visual analysis of research hotspots and trends in traditional Chinese medicine for depression in the 21st century: A bibliometric study based on citespace and VOSviewer. Heliyon, 2025; 11(1), e39785. https://doi.org/10.1016/j.heliyon.2024.e39785</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Акоев М.А. Картирование науки и технологии, прогноз развития. Руководство по наукометрии: индикаторы развития науки и технологии. Екатеринбург: Изд-во Уральского университета; 2014:164-184. https://doi.org/10.15826/B978-5-7996-1352-5.0007</mixed-citation><mixed-citation xml:lang="en">Stapleton, S., Dinsmore, C., Van Kleeck, D., &amp; Ma, X. Computer-assisted Indexing Complements Manual Selection of Subject Terms for Metadata in Specialized Collections. College &amp; Research Libraries, 2021; 82(6). https://doi.org/10.5860/crl.82.6.792</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Akoev M.A. Mapping science and technology, forecasting research and development. In: Handbook for Scientometrics: Indicators of Science and Technology Development. Ekaterinburg: Ural University Publ.; 2014:164-184. (In Russ.). https://doi.org/10.15826/B978-5-7996-1352-5.0007</mixed-citation><mixed-citation xml:lang="en">Tripathi M., Kumar S., Sonker S. K., Babbar, P. Occurrence of author keywords and keywords plus in social sciences and humanities research: A preliminary study. COLLNET Journal of Scientometrics and Information Management. 2018; 12(2): 215-232. https://doi.org/10.1080/09737766.2018.1436951</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Yang S., Han R., Wolfram D., Zhao Y. Visualizing the intellectual structure of information science (2006-2015): Introducing author keyword coupling analysis. Journal of Informetrics. 2016;10(1):132-150. https://doi.org/10.1016/j.joi.2015.12.003</mixed-citation><mixed-citation xml:lang="en">Uddin S., Khan A. The impact of author-selected keywords on citation counts. Journal of Informetrics. 2016; 10(4): 1166-1177. https://doi.org/10.1016/j.joi.2016.10.004</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Lu W., Huang S., Yang J., et al. Detecting research topic trends by author-defined keyword frequency. Information Processing &amp; Management. 2021;58(4):102594. https://doi.org/10.1016/j.ipm.2021.102594</mixed-citation><mixed-citation xml:lang="en">Gao, J., &amp; Wang, X. Exploring research hotspots and trends in the field of intelligent diagnosis and treatment from a bibliometric perspective: A comprehensive analysis of Citespace and VOSviewer. Proceedings of the 2024 5th International Symposium on Artificial Intelligence for Medicine Science, 2024; 108–113. https://doi.org/10.1145/3706890.3706908</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">González L.M., García-Massó X., Pardo-Ibañez A., Peset F., Devís-Devís J. An author keyword analysis for mapping Sport Sciences. PloS ONE. 2018;13(8):e0201435. https://doi.org/10.1371/journal.pone.0201435</mixed-citation><mixed-citation xml:lang="en">Wei, R. Z., Liu, X. Y., &amp; Lyu, P. H. Bibliometrics of public administration research hotspots: Topic keywords, author keywords, keywords plus analysis. Heliyon, 2024; 10(21). https://doi.org/10.1016/j.heliyon.2024.e39352</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Pearson W.S. Research topics in applied linguistics as keywords from authors and keywords from abstracts: A bibliometric study. In: Meihami H., Esfandiari R., eds. A Scientometrics Research Perspective in Applied Linguistics. Cham: Springer; 2024:113-134. https://doi.org/10.1007/978-3-031-51726-6_5</mixed-citation><mixed-citation xml:lang="en">Yang, S., Han, R., Wolfram, D., &amp; Zhao, Y. Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis. Journal of informetrics, 2016; 10(1): 132-150. https://doi.org/10.1016/j.joi.2015.12.003</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Gao J., Wang X. Exploring research hotspots and trends in the field of intelligent diagnosis and treatment from a bibliometric perspective: A comprehensive analysis of Citespace and VOSviewer. In: Proc. 2024 5th Int. Symp. on Artificial Intelligence for Medicine Science (ISAIMS 2024). (Amsterdam, August 13-17, 2024). New York, NY: Association for Computing Machinery; 2024:108-113. https://doi.org/10.1145/3706890.3706908</mixed-citation><mixed-citation xml:lang="en">Yang, J., Lu, W., Hu, J., &amp; Huang, S. A novel emerging topic detection method: A knowledge ecology perspective. Information Processing &amp; Management, 2022; 59(2), 102843. https://doi.org/10.1016/j.ipm.2021.102843</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Song C., Chen K., Jin Y., Chen L., Huang Z. Visual analysis of research hotspots and trends in traditional Chinese medicine for depression in the 21st century: A bibliometric study based on citespace and VOSviewer. Heliyon. 2025;11(1):e39785. https://doi.org/10.1016/j.heliyon.2024.e39785</mixed-citation><mixed-citation xml:lang="en">Yang J., Liu Z., Cheng X., Ye G. Understanding the keyword adoption behavior patterns of researchers from a functional structure perspective. Scientometrics. 2024; 129(6): 3359-3384. https://doi.org/10.1007/s11192-024-05031-1</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Nabilah N., Nakamo S.J., Mwakapemba M.L. Mapping the evolution of research themes on ChatGPT integration in education: Thematic and novelty keywords. Elementaria: Journal of Educational Research. 2025;3(1):34-44. https://doi.org/10.61166/elm.v3i1.90</mixed-citation><mixed-citation xml:lang="en">Zhang, J., Yu, Q., Zheng, F., Long, C., Lu, Z., &amp; Duan, Z. Comparing keywords plus of WOS  and author keywords: A case study of patient adherence research. Journal of the Association for Information Science and Technology, 2016; 67(4), 967–972. https://doi.org/10.1002/asi.23437</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Malvern D., Richards B., Chipere N., Durán P. Lexical Diversity and Language Development. London: Palgrave Macmillan; 2004. 253 p. https://doi.org/10.1057/9780230511804</mixed-citation><mixed-citation xml:lang="en">Akoev M.A. Mapping science and technology, forecasting research and development. Rukovodstvo po naukometrii: indikatory razvitiia nauki i tekhnologii / Guide to Scientometry: indicators of science and technology development. Ural University Publishing House.  2014; 164-184. (In Russ.) https://doi.org/10.15826/B978-5-7996-1352-5.0007</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">McCarthy P.M., Jarvis S. MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods. 2010;42(2):381-392. https://doi.org/10.3758/BRM.42.2.381</mixed-citation><mixed-citation xml:lang="en">Dubinina E.Yu. Selection of Keywords in a Scientific Article in the Process of Creating an Automatic Abstract. Vestnik Voronezhskogo gosudarstvennogo universiteta. Seriya: Filologiya. Zhurnalistika / Proceedings of Voronezh State University. Series: Philology. Journalism. 2020; (1): 26-28. (In Russ.). http://www.vestnik.vsu.ru/pdf/phylolog/2020/01/2020-01-06.pdf</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Powell J., Klein M., Balakireva L. Combining keyphrase extraction and lexical diversity to characterize ideas in publication titles (3; Version 1). arXiv. 2022. https://doi.org/10.48550/ARXIV.2208.13978</mixed-citation><mixed-citation xml:lang="en">Timoshenko I.V. The current trends in the development of methods and regulatory framework for indexing library information resources. Nauchnye I Tekhnicheskie biblioteki / Scientific and Technical Libraries. 2024; (10):102-122. (In Russ.). https://doi.org/10.33186/1027-3689-2024-10-102-122</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Yang J., Lu W., Hu J., Huang S. A novel emerging topic detection method: A knowledge ecology perspective. Information Processing &amp; Management. 2022;59(2):102843. https://doi.org/10.1016/j.ipm.2021.102843</mixed-citation><mixed-citation xml:lang="en">Tikhonova E.V., Kosycheva M.A. Effective Keywords: Strategies for their Formulation. Health, food &amp; biotechnology. 2021; 3(4): 7-15. (In Russ.) https://doi.org/10.36107/hfb.2021.i4.s122</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Тимошенко И.В. Современные тенденции развития методов и нормативной базы индексирования библиотечных информационных ресурсов. Научные и технические библиотеки. 2024;(10):102-122. https://doi.org/10.33186/1027-3689-2024-10-102-122</mixed-citation><mixed-citation xml:lang="en">Shcherbinina G.S. The philosophy of coordinate indexing. Nauchnye I Tekhnicheskie biblioteki / Scientific and Technical Libraries. 2000; (10):102-122. (In Russ.). https://www.gpntb.ru/win/ntb/ntb2000/9/f09_08.html</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Тихонова Е.В., Косычева М.А. Эффективные ключевые слова: стратегии формулирования. Health, Food &amp; Biotechnology. 2021;3(4):7-15. https://doi.org/10.36107/hfb.2021.i4.s122</mixed-citation><mixed-citation xml:lang="en">Тихонова Е.В., Косычева М.А. Эффективные ключевые слова: стратегии формулирования. Health, Food &amp; Biotechnology. 2021;3(4):7-15. https://doi.org/10.36107/hfb.2021.i4.s122</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
