Generational Patterns of Digital Research Activity: Age Dynamics and Publication Profiles within the Hungarian Academy of Sciences

Sasvári, Péter László and Hajdú, Noémi (2026) Generational Patterns of Digital Research Activity: Age Dynamics and Publication Profiles within the Hungarian Academy of Sciences. In: IEEE 24th World Symposium on Applied Machine Intelligence and Informatics (SAMI 2026). Institute of Electrical and Electronics Engineers (IEEE), Piscataway (NJ), pp. 275-282. ISBN 9798331591625

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Abstract

Understanding how digitalization and generational differences shape research engagement throughout an academic career is essential for sustaining vibrant scientific communities. This study examines digital publication activity among full and corresponding members of the Hungarian Academy of Sciences (MTA), whose intellectual and organizational roles influence national research policy and institutional evaluation. Focusing on outputs from 2020 to 2024, we analyzed records from the Hungarian Scientific Works Repository (MTMT), the Academy’s official digital bibliographic database. Indicators included total publications, language of output, independent citations, journal impact categories (Q1–Q4, D1), and co-authorship patterns. Pearson correlation tests explored links between age and each indicator within the Academy’s eleven scientific sections, and cluster analysis identified field-level publication profiles. Results show clear generational patterns of digital research productivity: activity remains high until retirement age but declines thereafter. Publication inactivity is rare before 65, yet rises steadily, exceeding 50% in some fields among scholars over 80. Negative correlations between age and international visibility (Q1, D1) are strongest in agricultural, medical, chemical, mathematical, biological, and earth sciences, but weaker in the humanities and social sciences. Physical sciences display exceptionally large-scale digital collaborations, with recent median author counting above 2,000, complicating individual-level evaluation. These findings provide an evidencebased view of how digital transformation intersects with academic age dynamics, supporting fair, field-sensitive policies for recognizing and sustaining scientific work across generations.

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