Multi-dimensional bibliometric framework for analyzing research adaptation during crisis: evidence from Ukrainian educational psychology

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 C v = 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. • Novel framework integrates network and semantic analysis. • 14 topics identified with 92.9% cross-method alignment. • Crisis adaptation observed within 6–8 months in corpus. • Semantic evolution tracked across key educational terms. • Replicable approach for global crisis research analysis.