Text Mining for Exploring Trends in Air Transport Research
Ulrike Schmalz,
Lukas Preis,
Annika Paul and
Marius Kleiser
Futures & Foresight Science, 2025, vol. 7, issue 2
Abstract:
This study applies text‐mining techniques to explore trends in scientific publications, using the air transport research domain as a case study. It detects trends using experts' assessments in a prestudy and examines the status of research in the scientific literature through text mining based on predeveloped keyword dictionaries. The text mining is executed using the ANTENAS toolbox developed at Bauhaus Luftfahrt, an aviation research think tank located in Germany. The findings reveal which trends are well covered by academia and where research gaps may exist. The paper offers a way to quantify the weight and growth (including volatile or “up‐and‐coming”) of trends as covered in the literature in relative terms over recent years. A keyword dictionary, transferable for other research purposes or for replicating the approach of this study, is provided as open access.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1002/ffo2.70016
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:fufsci:v:7:y:2025:i:2:n:e70016
Access Statistics for this article
More articles in Futures & Foresight Science from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().