Identifying skills in the Danish labor market
(2022) DABN01 20221Department of Statistics
Department of Economics
- Abstract
- Text analysis recently became a popular method to analyze the labor market in the field of research economics. This thesis uses an online Latent Dirichlet Allocation model to extract skills from two selected sectors of the Danish labor market between 2018 and 2021. The method uses topic modeling, where the keywords in the resulting topics are associated with skills, tasks or occupations. The resulting topics are represented in a two-dimensional, intertopic distance map. It is shown that skills, tasks, and words describing occupations can be extracted from the data. The possible use of intertopic disntances for determining the vulnerability of a sector to skill shortage is briefly discussed apart from the model results.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9083993
- author
- Nagy, Luca Sára LU
- supervisor
- organization
- course
- DABN01 20221
- year
- 2022
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- text analysis, labor market, LDA, NLP, topic modeling, online Latent Dirichlet Allocation
- language
- English
- id
- 9083993
- date added to LUP
- 2022-06-08 12:49:49
- date last changed
- 2022-10-10 16:04:06
@misc{9083993, abstract = {{Text analysis recently became a popular method to analyze the labor market in the field of research economics. This thesis uses an online Latent Dirichlet Allocation model to extract skills from two selected sectors of the Danish labor market between 2018 and 2021. The method uses topic modeling, where the keywords in the resulting topics are associated with skills, tasks or occupations. The resulting topics are represented in a two-dimensional, intertopic distance map. It is shown that skills, tasks, and words describing occupations can be extracted from the data. The possible use of intertopic disntances for determining the vulnerability of a sector to skill shortage is briefly discussed apart from the model results.}}, author = {{Nagy, Luca Sára}}, language = {{eng}}, note = {{Student Paper}}, title = {{Identifying skills in the Danish labor market}}, year = {{2022}}, }