The Transition from Higher Education to Employment in Romania: A Deep Understanding of the Job Market Using Text Analysis

Adriana AnaMaria Davidescu, Eduard Mihai Manta and Maria Ruxandra Cojocaru

A chapter in Contemporary Challenges in Social Science Management: Skills Gaps and Shortages in the Labour Market, 2024, vol. 112B, pp 69-86 from Emerald Group Publishing Limited

Abstract: Purpose:Students’ transition from education to employment is influenced by factors like the length and calibre of their education, demography, labour market conditions, and the general state of the economy. Regardless of the economy, education systems should seek to ensure that students have the skills required for the labour market. This will help them better transition from school to work. This study examines the work skills that companies require for entry-level positions in Romania. Need for Study:Previously, text analysis studies treated the job market only for the IT industry in Romania. To understand the demand-side opportunities and restrictions, assessing the employment opportunities for young people in the Romanian labour market is necessary. Methodology:A text mining approach from 842 unstructured data of the existing job positions in October 2022 for fresh graduates or students is used in this chapter. The study uses data from LinkedIn job descriptions in the Romanian job market. The methodology involved is focused on text retrieval, text-pre-processing, word cloud analysis, network analysis, and topic modelling. Findings:The empirical findings revealed that the most common words in job descriptions are experience, team, work, skills, development, knowledge, support, data, business, and software. The correlation network revealed that the most correlated pairs of words are gender–sexual–race–religion–origin–diversity–age–identity–orientation–colour–equal–marital. Practical Implications:This study looked at the job market and used text analytics to extract a space of skill and qualification dimensions from job announcements relevant to the Romanian employment market instead of depending on subjective knowledge.

Keywords: Text analysis; topic modelling; employment; education; job description; LinkedIn; Romanian labour market (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:csefzz:s1569-37592024000112b004

DOI: 10.1108/S1569-37592024000112B004

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