Soft Skills in the Wild: Challenges in Multilingual Classification
| Type of publication: | Conference paper |
| Citation: | Vasquez-Rodriguez_SOFTSKILLSINTHEWILD_2025 |
| Publication status: | Accepted |
| Booktitle: | Proceedings of the 10th edition of the Swiss Text Analytics Conference |
| Year: | 2025 |
| Month: | May |
| Abstract: | Soft skills are a crucial factor in candidate selection for recruitment. However, they are often overlooked due to the challenges in their identification. In this study, we compare soft and hard skills as well as occupations, both in terms of surface and semantic properties of the annotations and as part of an automatic extraction task, showing clear differences between the types of skills. Soft skills can be easily limited to a small number of categories, as we show in our annotation framework, which is based on well-known taxonomies. However, the way they are expressed in texts varies more widely than other entity types. These insights help to understand possible causes for the large variation in performance we see when using a multilingual BERT-based classifier for the identification of soft skills compared to other entities, which can help the community to develop more reliable algorithms for recruitment. |
| Keywords: | human resources, multilinguality, Natural language processing, nlp4hr, soft skills |
| Projects |
Idiap SEM24 |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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