  Recent years have brought significant advances to Natural Language Processing
(NLP), which enabled fast progress in the field of computational job market
analysis. Core tasks in this application domain are skill extraction and
classification from job postings. Because of its quick growth and its
interdisciplinary nature, there is no exhaustive assessment of this emerging
field. This survey aims to fill this gap by providing a comprehensive overview
of deep learning methodologies, datasets, and terminologies specific to
NLP-driven skill extraction and classification. Our comprehensive cataloging of
publicly available datasets addresses the lack of consolidated information on
dataset creation and characteristics. Finally, the focus on terminology
addresses the current lack of consistent definitions for important concepts,
such as hard and soft skills, and terms relating to skill extraction and
classification.
