Community analysis in Slovenian labour network 2010-2020

• Published in: Journal of decision systems Vol. 31; no. S1; pp. 308 - 318
• Main Authors: Andonovikj, Viktor, Boskoski, Pavle, Evkoski, Bojan, Redek, Tjaša, Mileva Boshkoska, Biljana
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 15.12.2022; Taylor & Francis Ltd
• Subjects: Algorithms; community detection; Decision making; directed network; Ensemble Louvain; Labour market; Occupations
• ISSN: 1246-0125; 2116-7052
• DOI: 10.1080/12460125.2022.2070944

There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.