From Data to Insight: Transforming Online Job Postings into Labor-Market Intelligence
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Published:2024-08-20
Issue:8
Volume:15
Page:496
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ISSN:2078-2489
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Container-title:Information
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language:en
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Short-container-title:Information
Author:
Tzimas Giannis1, Zotos Nikos2ORCID, Mourelatos Evangelos3, Giotopoulos Konstantinos C.2ORCID, Zervas Panagiotis1
Affiliation:
1. Data and Media Laboratory, Department of Electrical and Computer Engineering, University of Peloponnese, 22131 Tripoli, Greece 2. Department of Management Science and Technology, University of Patras, 26334 Patras, Greece 3. Department of Economics, Accounting and Finance, Oulu Business School, University of Oulu, FI-90014 Oulu, Finland
Abstract
In the continuously changing labor market, understanding the dynamics of online job postings is crucial for economic and workforce development. With the increasing reliance on Online Job Portals, analyzing online job postings has become an essential tool for capturing real-time labor-market trends. This paper presents a comprehensive methodology for processing online job postings to generate labor-market intelligence. The proposed methodology encompasses data source selection, data extraction, cleansing, normalization, and deduplication procedures. The final step involves information extraction based on employer industry, occupation, workplace, skills, and required experience. We address the key challenges that emerge at each step and discuss how they can be resolved. Our methodology is applied to two use cases: the first focuses on the analysis of the Greek labor market in the tourism industry during the COVID-19 pandemic, revealing shifts in job demands, skill requirements, and employment types. In the second use case, a data-driven ontology is employed to extract skills from job postings using machine learning. The findings highlight that the proposed methodology, utilizing NLP and machine-learning techniques instead of LLMs, can be applied to different labor market-analysis use cases and offer valuable insights for businesses, job seekers, and policymakers.
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