Abstract

ABSTRACT The emerging field of Labour Market Intelligence focuses on extracting real-time information for professional skills. Online job posting websites provide unique opportunities to gather such intelligence, useful for job seekers and academic administrators in charge of preparing the future labour force. We propose a probabilistic topic modelling approach, incorporating occupational ontologies, to extract skillsets required for jobs needing a Master of Business Administration (MBA) degree. Analysing LinkedIn job postings in Pennsylvania, USA, we identified 28 job functions and associated skillsets confirming known demands and revealing new ones not yet identified in government and private labour market reports. By aggregating these skills, we can align MBA curricula with market needs, offering a superior alternative to conventional surveys. Our results are comparable with other popular neural models. Our approach provides improved computational efficiency with simpler methods Additionally, this methodology can be applied globally in other fields with existing occupational ontologies.

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