Details
| Original language | English |
|---|---|
| Title of host publication | Handbook of Research Methods in Careers |
| Publisher | Edward Elgar Publishing Ltd. |
| Pages | 139-163 |
| Number of pages | 25 |
| ISBN (electronic) | 9781788976725 |
| ISBN (print) | 9781788976718 |
| Publication status | Published - 8 Jun 2021 |
| Externally published | Yes |
Abstract
The abundance of unstructured data, primarily consisting of text, coupled with the development of modern techniques to analyze them, offer new opportunities for theory generation, theory testing, and contextualization within the field of career studies. This chapter explains the process of text mining as it may be applied to the study of careers, starting with text preprocessing and ending with the application of analytical techniques. Both conventional techniques such as latent semantic and principal components analysis, and more novel text analytical techniques such as word embeddings are discussed with the hope of inspiring careers researchers to further embrace text analysis as a means to answer novel research questions. Furthermore, this chapter elaborates on how to evaluate the validity of information extracted from text. In order to illustrate the text analytical process, we provide an example that leverages an abundant and growing source of data that may be of interest to career researchers, namely, vacancy data. In the example, vacancy data are used to identify those knowledge, skills and abilities that (co)determine the salary associated with particular occupations. We end the chapter by providing a guide on how text mining can be applied to study existing and new career concepts.
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)
- General Business,Management and Accounting
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
Handbook of Research Methods in Careers. Edward Elgar Publishing Ltd., 2021. p. 139-163.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Text mining in career studies
T2 - Generating insights from unstructured textual data1
AU - Kobayashi, Vladimer B.
AU - Mol, Stefan T.
AU - Vrolijk, Jarno
AU - Kismihók, Gábor
PY - 2021/6/8
Y1 - 2021/6/8
N2 - The abundance of unstructured data, primarily consisting of text, coupled with the development of modern techniques to analyze them, offer new opportunities for theory generation, theory testing, and contextualization within the field of career studies. This chapter explains the process of text mining as it may be applied to the study of careers, starting with text preprocessing and ending with the application of analytical techniques. Both conventional techniques such as latent semantic and principal components analysis, and more novel text analytical techniques such as word embeddings are discussed with the hope of inspiring careers researchers to further embrace text analysis as a means to answer novel research questions. Furthermore, this chapter elaborates on how to evaluate the validity of information extracted from text. In order to illustrate the text analytical process, we provide an example that leverages an abundant and growing source of data that may be of interest to career researchers, namely, vacancy data. In the example, vacancy data are used to identify those knowledge, skills and abilities that (co)determine the salary associated with particular occupations. We end the chapter by providing a guide on how text mining can be applied to study existing and new career concepts.
AB - The abundance of unstructured data, primarily consisting of text, coupled with the development of modern techniques to analyze them, offer new opportunities for theory generation, theory testing, and contextualization within the field of career studies. This chapter explains the process of text mining as it may be applied to the study of careers, starting with text preprocessing and ending with the application of analytical techniques. Both conventional techniques such as latent semantic and principal components analysis, and more novel text analytical techniques such as word embeddings are discussed with the hope of inspiring careers researchers to further embrace text analysis as a means to answer novel research questions. Furthermore, this chapter elaborates on how to evaluate the validity of information extracted from text. In order to illustrate the text analytical process, we provide an example that leverages an abundant and growing source of data that may be of interest to career researchers, namely, vacancy data. In the example, vacancy data are used to identify those knowledge, skills and abilities that (co)determine the salary associated with particular occupations. We end the chapter by providing a guide on how text mining can be applied to study existing and new career concepts.
UR - http://www.scopus.com/inward/record.url?scp=85129419305&partnerID=8YFLogxK
U2 - 10.4337/9781788976725.00015
DO - 10.4337/9781788976725.00015
M3 - Contribution to book/anthology
AN - SCOPUS:85129419305
SN - 9781788976718
SP - 139
EP - 163
BT - Handbook of Research Methods in Careers
PB - Edward Elgar Publishing Ltd.
ER -