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Identifying skills in the Danish labor market

Nagy, Luca Sára LU (2022) DABN01 20221
Department 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.
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author
Nagy, Luca Sára LU
supervisor
organization
course
DABN01 20221
year
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}},
}