TY - JOUR
T1 - Text mining on job advertisement data
T2 - 1st Workshop on AI + Informetrics, AII 2021
AU - Bäck, Asta
AU - Hajikhani, Arash
AU - Suominen, Arho
N1 - Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870822
Funding Information:
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 870822.
Publisher Copyright:
© 2021 CEUR-WS. All rights reserved.
PY - 2021
Y1 - 2021
N2 - The use of online job advertisement has made them an important source of quantitative information about the innovation system. This data offers significant opportunities to study trends, transitions in the job markets and skill demands. In this study, we have utilized the job ads data of a major Finnish job market platform to investigate the emergence of AI-related jobs. More than 480 000 job advertisements during 2013-2020 was used to create insight on skills transitions, particularly focusing on artificial intelligence related skills. A glossary of AI-related skills was created and applied to the job data to identify the relatedness spectrum of ads to AI using a three-tier system. By incorporating sectoral firm-level information, we explored the variation in AI-related skills demand over time and sectors. Our study presents a systematic way to utilize job advertisement data for detecting demand trends for specific skills.
AB - The use of online job advertisement has made them an important source of quantitative information about the innovation system. This data offers significant opportunities to study trends, transitions in the job markets and skill demands. In this study, we have utilized the job ads data of a major Finnish job market platform to investigate the emergence of AI-related jobs. More than 480 000 job advertisements during 2013-2020 was used to create insight on skills transitions, particularly focusing on artificial intelligence related skills. A glossary of AI-related skills was created and applied to the job data to identify the relatedness spectrum of ads to AI using a three-tier system. By incorporating sectoral firm-level information, we explored the variation in AI-related skills demand over time and sectors. Our study presents a systematic way to utilize job advertisement data for detecting demand trends for specific skills.
UR - http://www.scopus.com/inward/record.url?scp=85107593426&partnerID=8YFLogxK
UR - http://ceur-ws.org/
M3 - Article in a proceedings journal
AN - SCOPUS:85107593426
SN - 1613-0073
VL - 2871
SP - 111
EP - 124
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 17 March 2021 through 17 March 2021
ER -