Text Mining for Exploring Trends in Air Transport Research

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.