用数字语义评分衡量数字劳动力市场转型：一种应用于荷兰劳动力市场的 AI 方法

Computer Science > Computation and Language arXiv:2608.24222 (cs) [Submitted on 25 Aug 2026 (v1), last revised 18 Sep 2026 (this version, v2)] Title:Measuring Digital Labour Market Transitions with a Digital Semantic Score: An AI-Based Methodology Applied to the Dutch Labour Market Authors:Sadegh Shahmohammadi, Xavier Pinho, Mairi Bowdler, Suhendan Adiguzel-van Zoelen, Joost van Genabeek View a PDF of the paper titled Measuring Digital Labour Market Transitions with a Digital Semantic Score: An AI-Based Methodology Applied to the Dutch Labour Market, by Sadegh Shahmohammadi and 4 other authors View PDF Abstract:The digital transformation of the Dutch labour market is reshaping occupational language, career pathways, and job-related skills. Addressing these changes requires granular labour market intelligence. This paper develops an AI-based methodology to analyse digitalisation using data covering millions of Dutch job profiles. The methodology combines embedding-based similarity search and large language model classification to map unstructured job information to harmonised ESCO occupations. We also introduce a Digital Semantic Score that measures how strongly job titles and skills are associated with digital concepts relative to a non-digital reference. Using embeddings and cosine similarity to transparent digital and non-digital anchor groups, this indicator moves beyond keyword-based approaches by capturing broader digital meanings in occupational language and worker skill profiles. It enables analysis across occupations, career transitions, emerging job-title vocabulary, and skill digitality. The findings reveal that digitalisation is unevenly distributed across the labour market. Digital job-title language is most prominent among managerial, professional and ICT-related occupations, but is increasingly visible in hybrid business, marketing and automation-related roles. Career-transition analyses show that movement toward digital work is pathway-dependent, while skill analyses highlight the multidimensional nature of digital capability, encompassing technical, hybrid and business-systems skills. By combining profile data, AI-supported occupational classification and semantic scoring, this study advances AI-driven labour market analytics and provides a scalable framework for monitoring digital labour market change. The methodology helps identify emerging skill needs, support reskilling strategies, and inform policies addressing skills mismatches and labour shortages in the Netherlands. Subjects: Computation and Language (cs.CL) Cite as: arXiv:2608.24222 [cs.CL] (or arXiv:2608.24222v2 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2608.24222 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Sadegh Shahmohammadi [view email] [v1] Tue, 25 Aug 2026 08:27:35 UTC (1,127 KB) [v2] Fri, 18 Sep 2026 09:48:13 UTC (1,144 KB) Full-text links: Access Paper: View a PDF of the paper titled Measuring Digital Labour Market Transitions with a Digital Semantic Score: An AI-Based Methodology Applied to the Dutch Labour Market, by Sadegh Shahmohammadi and 4 other authors View PDF view license Current browse context: cs.CL new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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