An empirical analysis of incentive structures in German online job advertisements using a topic modeling approach (original) (raw)

Zusammenfassung

In light of the imminent labor shortage, companies find themselves compelled to enhance their standing as desirable employers in the competitive pursuit of talent. This endeavor can be facilitated through the medium of online job advertisements (OJAs), which serve as a means to subtly communicate the merits of an organization to prospective employees. The objective of this study is to develop and evaluate a topic-modeling approach, known as Latent Dirichlet Allocation (LDA), for analyzing online data. The study will also discuss the strengths and weaknesses of the approach. The work will also include considerations on social sciences theory, signaling theory, and methods will be evaluated.

Gassner, Michelle Katharina; Tiemann, Michael; Dörpinghaus, Jens (2025): An empirical analysis of incentive structures in German online job advertisements using a topic modeling approach. INFORMATIK 2025. DOI: 10.18420/inf2025_87. Bonn: Gesellschaft für Informatik e.V.. PISSN: 2944-7682. pp. 1023. Digitalization and AI for Society, in Education and Educational Research (DAI-EAR'25). Potsdam. 16.–19. September 2025