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http://ds.knu.edu.ua/jspui/handle/123456789/9309Повний запис метаданих
| Поле DC | Значення | Мова |
|---|---|---|
| dc.contributor.author | Semerikov, Serhiy O. | - |
| dc.contributor.author | Mintii, Iryna S. | - |
| dc.date.accessioned | 2026-07-12T08:51:45Z | - |
| dc.date.available | 2026-07-12T08:51:45Z | - |
| dc.date.issued | 2026-03-24 | - |
| dc.identifier.citation | Multi-dimensional bibliometric framework for analyzing research adaptation during crisis: evidence from Ukrainian educational psychology / Serhiy O. Semerikov, Iryna S. Mintii // Social Sciences & Humanities Open. – 2026. – Volume 13. – Article 102709. – https://doi.org/10.1016/j.ssaho.2026.102709 | uk_UA |
| dc.identifier.issn | 2590-2911 | - |
| dc.identifier.uri | https://doi.org/10.1016/j.ssaho.2026.102709 | - |
| dc.identifier.uri | http://ds.knu.edu.ua/jspui/handle/123456789/9309 | - |
| dc.description | Barber, B. K. (2013). Annual research review: The experience of youth with political conflict - challenging notions of resilience and encouraging research refinement. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54, 461–473. https://doi.org/10.1111/jcpp.12056 Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022. https://www.jmlr.org/papers/v3/blei03a.html. Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18, 50. https://doi.org/10.1186/s41239-021-00282-x Bouillet, D., & Jokić, M. (2019). Characteristics of educational sciences research activity in european post-socialist countries in the period 1996 to 2013: Content analysis approach. European Educational Research Journal, 18, 407–425. https://doi.org/10.1177/1474904119827462 Bozkurt, A., Karakaya, K., Turk, M., Karakaya, Ö., & Castellanos-Reyes, D. (2022). The impact of COVID-19 on education: A meta-narrative review. TechTrends, 66, 883–896. https://doi.org/10.1007/s11528-022-00759-0 Chen, C., & Song, M. (2019). Visualizing a field of research: A methodology of system atic scientometric reviews. PLoS ONE, 14, e0223994. https://doi.org/10.1371/journal.pone.0223994 Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 Ersozlu, Z., Taheri, S., & Koch, I. (2024). A review of machine learning methods used for educational data. Education and Information Technologies, 29, 22125–22145. https://doi.org/10.1007/s10639-024-12704-0 Kenworthy, A. L., Chekh, M., Kozlova, V., Opatska, S., Shestak, A., Trevoho, O., Tychenko, M., & Tytarenko, M. (2025). ‘see us’: An urgent call to collaborate with colleagues in crisis environments around the world. Teaching in Higher Education, 30, 544–554. https://doi.org/10.1080/13562517.2024.2372574 Kraus, S., Breier, M., Lim, W. M., Dabić, M., Kumar, S., Kanbach, D., Mukherjee, D., Corvello, V., Piñeiro-Chousa, J., Liguori, E., Palacios-Marqués, D., Schiavone, F., Ferraris, A., Fernandes, C., & Ferreira, J. J. (2022). Literature reviews as independent studies: Guidelines for academic practice. Review of Managerial Science, 16, 2577–2595. https://doi.org/10.1007/s11846-022-00588-8 Lordos, A., & Hyslop, D. (2021). The assessment of multisystemic resilience in Conflict-Affected populations. In M. Ungar (Ed.), Multisystemic resilience: Adaptation and transformation in contexts of change (pp. 417–451). New York: Oxford University Press. https://doi.org/10.1093/oso/9780190095888.003.0023 Röder, M., Both, A., & Hinneburg, A. (2015). Exploring the space of topic coherence measures. In Proceedings of the Eighth ACM International Conference on web search and data mining (pp. 399–408). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/2684822.2685324 Salih, A. M. F. Z. (2024). Impacts of armed conflicts on education: Challenges and pathways to recovery. Revista de Gestao Social e Ambiental, 18, e08466. https://doi.org/10.24857/rgsa.v18n8-169 Schui, G., & Krampen, G. (2007). On the internationality of educational psychology from the German-speaking countries: Scientist- and discipline-centered bibliometric publication and citation analyses. Zeitschrift fur Padagogische Psychologie, 21, 97–106. https://doi.org/10.1024/1010-0652.21.2.97 Semerikov, S. O., Nechypurenko, P. P., Vakaliuk, T. A., & Mintii, I. S. (2026). Resilience through crisis: An integrated framework for entrepreneurial STEM education in conflict-affected contexts. Discover Education, 5, 24. https://doi.org/10.1007/s44217-025-01041-0 Semerikov, S. O., Vakaliuk, T. A., Mintii, I. S., & Didkivska, S. O. (2023). Challenges facing distance learning during martial law: Results of a survey of Ukrainian students. Educational Technology Quarterly, 2023, 401–421. https://doi.org/10.55056/etq.637 van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84, 523–538. https://doi.org/10.1007/s11227-009-0273-0 Vayansky, I., & Kumar, S. A. P. (2020). A review of topic modeling methods. Information Systems, 94, 101582. https://doi.org/10.1016/j.is.2020.101582 | uk_UA |
| dc.description.abstract | This study presents a multi-dimensional bibliometric framework for analyzing research adaptation during crisis, demonstrated through the analysis of 487 publications from the Bulletin of Alfred Nobel University: Series Pedagogy and Psychology (2017–2024). Integrating VOSviewer term co-occurrence analysis with Latent Dirichlet Allocation (LDA) topic modeling, we develop a novel approach that captures both structural and semantic dimensions of research evolution. The analysis reveals 14 coherent topics (coherence score = 0.364, optimal among 8–20 topic configurations tested) organized into 10 thematic clusters, with pronounced shifts following the 2022 crisis onset. Our framework demonstrates notable research adaptation within this corpus, with crisis-related topics showing increased prevalence within 6–8 months of the crisis onset. Topic modeling reveals semantic evolution in key terms, with “adaptation” shifting from educational to psychological crisis contexts. The convergence of findings across analytical methods (92.9% alignment between LDA topics and VOSviewer clusters after robustness checks excluding high-frequency terms) validates the framework’s reliability. This methodological innovation offers a replicable approach for analyzing research dynamics in crisis-affected publication venues, contributing both methodological tools and empirical insights into academic adaptation patterns. Findings should be interpreted as reflecting this specific journal corpus rather than the entire national field. | uk_UA |
| dc.language.iso | en | uk_UA |
| dc.publisher | Elsevier | uk_UA |
| dc.subject | Bibliometric analysis | uk_UA |
| dc.subject | Topic modeling | uk_UA |
| dc.subject | Crisis adaptation | uk_UA |
| dc.subject | Research evolution | uk_UA |
| dc.subject | Multi-dimensional framework | uk_UA |
| dc.subject | Educational resilience | uk_UA |
| dc.title | Multi-dimensional bibliometric framework for analyzing research adaptation during crisis: evidence from Ukrainian educational psychology | uk_UA |
| dc.type | Article | uk_UA |
| dc.identifier.doi | https://doi.org/10.1016/j.ssaho.2026.102709 | - |
| local.submitter.email | semerikov@ccjourn... | uk_UA |
| Розташовується у зібраннях: | Кафедра професійної та соціально-гуманітарної освіти | |
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|---|---|---|---|---|
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