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Towards explicit soft skills labelling in ESCO through semantic NLP analysis

Author

Listed:
  • Ciprian Panzaru

    (West University of Timisoara)

  • Anamaria Grama

    (West University of Timisoara)

Abstract

The classification and identification of soft skills within the European Skills, Competences, Qualifications, and Occupations (ESCO) framework presents a significant challenge, as ESCO does not explicitly indicate which of its listed skills are considered “soft”. This lack of clear labelling complicates the strategic alignment of educational programs and workforce development initiatives with the evolving demands of today’s labour market, where soft skills are increasingly recognised as essential for professional success. Our study seeks to address this challenge by conducting a systematic literature review to identify and define a comprehensive set of soft skills, and by employing Natural Language Processing (NLP) techniques to map these skills to the ESCO taxonomy. Through semantic analysis and comparison of soft skills identified from scientific literature against the ESCO skillset, we establish a refined classification that explicitly labels soft skills within the ESCO framework. Our findings provide a necessary clarification of soft skills within the standardised European context, offering valuable insights for policymakers, educators, and HR professionals focused on fostering soft skills development. By clarifying the soft skills embedded within the ESCO framework, this research contributes to the advancement of skill taxonomies and promotes a more integrated approach to the development and assessment of soft skills. JEL classification J20, J24, I26, C88.

Suggested Citation

  • Ciprian Panzaru & Anamaria Grama, 2025. "Towards explicit soft skills labelling in ESCO through semantic NLP analysis," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 59(1), pages 1-13, December.
    • Handle: RePEc:spr:jlabrs:v:59:y:2025:i:1:d:10.1186_s12651-025-00409-x
    DOI: 10.1186/s12651-025-00409-x
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    References listed on IDEAS

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    1. Jiří Balcar, 2016. "Is it better to invest in hard or soft skills?," The Economic and Labour Relations Review, , vol. 27(4), pages 453-470, December.
    2. Heckman, James J. & Kautz, Tim, 2012. "Hard evidence on soft skills," Labour Economics, Elsevier, vol. 19(4), pages 451-464.
    3. Phillip Toner, 2011. "Workforce Skills and Innovation: An Overview of Major Themes in the Literature," OECD Science, Technology and Industry Working Papers 2011/1, OECD Publishing.
    4. Valentina Dolce & Federica Emanuel & Maurizio Cisi & Chiara Ghislieri, 2020. "The soft skills of accounting graduates: perceptions versus expectations," Accounting Education, Taylor & Francis Journals, vol. 29(1), pages 57-76, January.
    5. Phillip Toner, 2011. "Workforce Skills and Innovation: An Overview of Major Themes in the Literature," OECD Education Working Papers 55, OECD Publishing.
    6. Chiara Succi, 2019. "Are you ready to find a job? Ranking of a list of soft skills to enhance graduates' employability," International Journal of Human Resources Development and Management, Inderscience Enterprises Ltd, vol. 19(3), pages 281-297.
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    Keywords

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    JEL classification:

    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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