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Disciplinary Profiles of Local Topics in the Flemish Social Sciences and HumanitiesOA

中文摘要

Purpose:The study examines how local topics in the Flemish Academic Bibliographic Database for the Social Sciences and Humanities(VABB-SHW)are positioned within a disciplinary framework.It explores their size,language profile,and disciplinary profiles compared to the broader topic landscape.Design/methodology/approach:Topics were extracted using the clustering strategy of(Guns,R.2024.“A Bibliometric Map of Local Research in the Social Sciences and Humanities.”In Research Evaluatuion in Social Sciences and Humanities 2024.Galway,Ireland)with BERTopic,combining multilingual embeddings,UMAP dimensionality reduction,and HDBSCAN.Descriptions were generated with GPT-4o-mini,labelled with Gemini-2.5-Flash,and classified with a content-based model trained on Web of Science data and applied to VABB-SHW(Arhiliuc,C.,R.Guns,and T.C.E.Engels.2025b.“Text-Based Classification of all Social Sciences and Humanities Publications Indexed in the Flemish VABB Database.”In Proceedings of the 20th International Conference on Scientometrics&Informetrics(ISSI,2025)).Findings:Out of 517 topics,76(17.2%of publications)were identified as local.They contain more non-English publications,and cluster mainly in“History”,“Law”,“Literature”,“Political science”,and“Art”.Contrasts emerge in their profiles:“Law”topics are internally consistent,“History”topics diffuse across disciplines,and“Literature”is consistently classified when modal but tends to be overattributed otherwise.Research limitations/implications:The results reflect the scope of VABB-SHW and the narrow definition of“local”.Topic descriptions and disciplinary expectations may introduce uncertainty.The findings are not directly generalizable,but the approach can be replicated in other national databases and with broader definitions to test robustness.Practical implications:The approach illustrates how national bibliographic databases can be systematically analysed to identify and profile locally anchored research,offering a basis for comparative studies across regions.Originality/value:This is the first study to systematically analyse local topics in VABB-SHW,combining topic modelling and content-based classification to highlight how SSH research engages with nationally specific issues.

Cristina Arhiliuc;Raf Guns;Tim C.E.Engels

Centre for R&D Monitoring(ECOOM),University of Antwerp,Antwerp,BelgiumAnet Library Automation and Centre for R&D Monitoring(ECOOM),University of Antwerp,Antwerp,BelgiumCentre for R&D Monitoring(ECOOM),University of Antwerp,Antwerp,Belgium

社会科学

topic analysislocal topicsSSHresearch classificationVABB-SHW

《Journal of Data and Information Science》 2026 (2)

P.140-153,14

funded by the Flemish Government as part of the funding allocated to the Expertisecentrum Onderzoek&Ontwikkelingsmonitoring(ECOOM,Centre for Research&Development Monitoring)(OZ3631)The work of Raf Guns on topic extraction and annotation was supported by the National Natural Science Foundation of China(No.72274139).

10.1515/jdis-2025-0342

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