Responsible team players wanted: an analysis of soft skill requirements in job advertisements

Federica Calanca*, Luiza Sayfullina, Lara Minkus, Claudia Wagner, Eric Malmi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)
269 Downloads (Pure)


During the past decades the importance of soft skills for labour market outcomes has grown substantially. This carries implications for labour market inequality, since previous research shows that soft skills are not valued equally across race and gender. This work explores the role of soft skills in job advertisements by drawing on methods from computational science as well as on theoretical and empirical insights from economics, sociology and psychology. We present a semi-automatic approach based on crowdsourcing and text mining for extracting a list of soft skills. We find that soft skills are a crucial component of job ads, especially of low-paid jobs and jobs in female-dominated professions. Our work shows that soft skills can serve as partial predictors of the gender composition in job categories and that not all soft skills receive equal wage returns at the labour market. Especially “female” skills are frequently associated with wage penalties. Our results expand the growing literature on the association of soft skills on wage inequality and highlight their importance for occupational gender segregation at labour markets.

Original languageEnglish
Article number13
Pages (from-to)1-20
JournalEPJ Data Science
Issue number1
Publication statusPublished - 27 Apr 2019
MoE publication typeA1 Journal article-refereed


  • Computational social science
  • Crowdsourcing
  • Gender inequality
  • Job advertisement
  • Labour markets
  • Soft skills
  • Text mining


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  • Soft Skills list

    Calanca, F. (Creator), Sayfullina, L. (Creator), Minkus, L. (Creator), Malmi, E. (Creator) & Wagner, C. (Creator), SowiDataNet, 2019


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