Visualisation of professional skills by analysing advertisements on job sites
DOI:
https://doi.org/10.32480/rscp.2026.e3102Keywords:
professional skills, job advertisements, job portals, web scraping, social network analysisAbstract
The transformation of the labor market driven by technological advances requires continuous updating of university curricula.Therefore, this study identifies the most demanded professional skills across different degree programs of an Engineering Faculty by analyzing job advertisements published on the Indeed portal in Ecuador. A total of 512 job postings were collected throughweb scraping techniques, from which 755 professional skills were identified. Data was analyzed using Social Network Analysis (SNA), constructing networks that relate skills to areas of knowledge. The results reveal networks with low density, indicating high specialization and dispersion of the demanded competencies. Nevertheless, nodes with high centrality were identified, mainly associated with software development and data management, highlighting skills such as Java, SQL, JavaScript, and database management, particularly in Systems Engineering and Software Engineering. In other programs, specific patterns related to specialized technical tools were observed, including AutoCAD in Architecture and Mechanical Engineering, and ArcGIS and MapInfo in Environmental Engineering. These findings allow the characterization of skill demand according to each area of knowledge and provide empirical evidence to support curriculum updating processes, strengthening the alignment between academic training and current labor market needs. The proposed approach demonstrates methodological applicability for similarstudies in other national contexts.
Downloads
References
1. Stefanik M, Lyócsa Š, Bilka M. Using online job postings to predict key labour market indicators. Soc Sci Comput Rev. 2023;41:1630–49.
2. Adecco, Infoempleo. Informe Infoempleo & Adecco 2020. The Adecco Group. España; 2021.
3. Apatsidis I, Georgiou K, Mittas N, Angelis L. A Study of Remote and On-site ICT Labor Market Demand using Job Offers from Stack Overflow. Euromicro Conference on Software Engineering and Advanced Applications. 2021;252–9. Disponible en: https://ieeexplore.ieee.org/document/9582599
4. Schultheiss T, Backes-Gellner U. Does updating education curricula accelerate technology adoption in the workplace? Evidence from dual vocational education and training curricula in Switzerland. Journal of Technology Transfer. Springer US; 2024;49:191–235. Disponible en: https://link.springer.com/article/10.1007/s10961-022-09971-9
5. Jimenez Chaves VE, García Torres M. Análisis de la Educación Inicial en Paraguay a través de las Técnicas de Aprendizaje Automático. Revista de la Sociedad Científica del Paraguay. 2019;24(2):293–304. Disponible en: https://sociedadcientifica.org.py/ojs/index.php/rscpy/article/view/85/80
6. Kim YA, Kim KA, Tzokas N. Entrepreneurial universities and the effect of the types of vocational education and internships on graduates’ employability. Studies in Higher Education. 2022;47(5):1000–9. Disponible en: https://repository.essex.ac.uk/32772/1/Final%20Submission%20SHE%20SI_KimKimTzokas.pdf
7. Guerra DDD, Gamboa AJP, Cano CAG. Social network analysis in virtual educational environments: Implications for collaborative learning and academic community development. Awari. 2023;4:1–12. Disponible en: https://awari.pro-metrics.org/index.php/a/article/view/59
8. Yao Q, Li RYM, Song L, Crabbe MJC. Safety knowledge sharing on Twitter: A social network analysis. Saf Sci. 2021;143:105411.
9. Pascual-Ferrá P, Alperstein N, Barnett DJ. Social Network Analysis of COVID-19 Public Discourse on Twitter: Implications for Risk Communication. Disaster Med Public Health Prep. 2022;16(2):561–9. Disponible en: https://doi.org/10.1017/dmp.2020.347
10. Ponce J, Vicuña A, Erazo O, Samaniego E. Caracterización de factores que influyen en la baja producción científica de las universidades usando análisis de redes sociales. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao. 2019;(E17):156 – 169. Disponible en: 354087364_Caracterizacion_de_factores_que_influyen_en_la_baja_produccion_cientifica_de_las_universidades_usando_analisis_de_redes_sociales
11. Chang V, Hall K, Xu QA, Doan LMT, Wang Z. A social network analysis of two networks: Adolescent school network and Bitcoin trader network. Decision Analytics Journal. 2022;3:100065. Disponible en: https://pure.aston.ac.uk/ws/portalfiles/portal/84494824/1_s2.0_S2772662222000236_main.pdf
12. Romanko O, O’mahony M. The Use of Online Job Sites for Measuring Skills and Labour Market Trends: A Review. Economic Statistic Centre of Excellence (ESCoE). 2022. Disponible en: https://ideas.repec.org/p/nsr/escoet/escoe-tr-19.html
13. Milovanović S, Bogdanović Z, Labus A, Despotović-Zrakić M, Mitrović S. Social recruiting: an application of social network analysis for preselection of candidates. Data Technologies and Applications. 2022;ahead-of-p. Disponible en: 358591024_Social_recruiting_an_application_of_social_network_analysis_for_preselection_of_candidates
14. Kumar N, Gupta M, Sharma D, Ofori I. Technical Job Recommendation System Using APIs and Web Crawling. Comput Intell Neurosci. 2022. Disponible en: https://doi.org/10.1155/2022/7797548
15. Ming D, Lee Y, Wei D, Ang X, Mei G, Pua C, et al. A Social Network Analysis of Jobs and Skills. In: Institutional Knowledge at Singapore Management University A social network analysis of jobs and skills. 2020:5747–9. Disponible en: https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6651&context=sis_research
16. Suleman F, Suleman A, Cunha F. Employability skills of graduates: Insights from job advertisements. International Conference on Higher Education Advances. 2020:247–54.
17. Walek B, Pektor O. Data mining of job requirements in online job advertisements using machine learning and sdca logistic regression. Mathematics. 2021;9(19). Disponible en: https://doi.org/10.3390/math9192475
18. Lipovac I, Babac M. Content Analysis of Job Advertisements for Identifying Employability Skills. Interdisciplinary Description of Complex Systems. 2021;19(4):511–25.
19. Graham CM, Lu Y. Skills Expectations in Cybersecurity: Semantic Network Analysis of Job Advertisements. Journal of Computer Information Systems. 2022;63(4):1–13.
20. Maghsoudi M. Uncovering the skillsets required in computer science jobs using social network analysis. Educ Inf Technol (Dordr). 2024;29(10):12759–80. Disponible en: https://arxiv.org/abs/2308.08582
21. Guerrero Herrera LA, Cordero AT, Torres YS. Global Labour Skills Market from Network Theory. Redes. 2023;34(2):254–65. Disponible en: https://dialnet.unirioja.es/servlet/articulo?codigo=8926863
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Revista de la Sociedad Científica del Paraguay
This work is licensed under a Creative Commons Attribution 4.0 International License.
El/los autores autorizan a la Revista de la Sociedad Científica del Paraguay a publicar y difundir el articulo del cual son autores, por los medios que considere apropiado.
