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Research Brief
Developing a New Method to Uncover Skills Trends in Emerging Economies Using Online Data and NLP techniques
This research brief outlines a novel methodology using online big data and natural language processing (NLP) to analyze transferable skills trends across diverse sectors and countries, offering insights into skills demand, supply, mismatches, and their relationship to job quality and transitions.
This methodological brief describes an innovative approach that exploits online big data from job vacancies and applicants' profiles and utilizes natural language processing (NLP) to extract information on skills.
The approach is based on a taxonomy comprising 15 unique skills subcategories across the broader cognitive, socio-emotional, and manual skills categories. It focuses on skills that are transferable rather than occupation-specific.
So far tested with data on Uruguay, Brazil, the Russian Federation, and South Africa, the method is applicable to countries of all income levels and allows detecting country-specific skills trends. It captures a wide range of sectors and occupations, including those requiring manual labour.
It can be used to offer novel insights into skills demand, supply and mismatch, as well as into the relationship between skills and aspects of job quality and/or job transitions.
