Using online vacancy and job applicants’ data to study skills dynamics
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Organización Internacional del Trabajo (OIT)
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| Format: | Entrada de enciclopedia |
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International Labour Organization
2022
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| author | Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann |
| author_facet | Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann |
| contents | Using online vacancy and job applicants’ data to study skills dynamics Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann This paper finds that big data on vacancies and applications to an online job board can be a promising data source for studying skills dynamics, especially in countries where alternative sources are scarce. To show this, we develop a skills taxonomy, assess the characteristics of such online data, and employ natural language processing and machine-learning techniques. The empirical implementation uses data from the Uruguayan job board BuscoJobs, but can be replicated with similar data from other countries. ILO working paper, 75, ILO 10.54394/EWWE6877 DOI https://doi.org/10.54394/EWWE6877; ISBN 9789220376638,9789220376614 publication.encyclopediaEntry |
| format | Entrada de enciclopedia |
| id | ilo_995218815602676 |
| institution | Organización Internacional del Trabajo (OIT) |
| publishDate | 2022 |
| publisher | International Labour Organization |
| spellingShingle | Using online vacancy and job applicants’ data to study skills dynamics Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann Using online vacancy and job applicants’ data to study skills dynamics Fidel Bennett (Author) Verónica Escudero (Author) Ana Podjanin (Author) Hannah Liepmann This paper finds that big data on vacancies and applications to an online job board can be a promising data source for studying skills dynamics, especially in countries where alternative sources are scarce. To show this, we develop a skills taxonomy, assess the characteristics of such online data, and employ natural language processing and machine-learning techniques. The empirical implementation uses data from the Uruguayan job board BuscoJobs, but can be replicated with similar data from other countries. ILO working paper, 75, ILO 10.54394/EWWE6877 DOI https://doi.org/10.54394/EWWE6877; ISBN 9789220376638,9789220376614 publication.encyclopediaEntry |
| title | Using online vacancy and job applicants’ data to study skills dynamics |
| url | https://researchrepository.ilo.org/esploro/outputs/encyclopediaEntry/Using-online-vacancy-and-job-applicants/995218815602676 |