Analysing Online Vacancy and Skills Demand using Text Mining

• Published in: Journal of Physics: Conference Series
• Main Author: Nasir S.A.M.; Wan Yaacob W.F.; Wan Aziz W.A.H.
• Format: Conference paper
• Language: English
• Published: Institute of Physics Publishing 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086713854&doi=10.1088%2f1742-6596%2f1496%2f1%2f012011&partnerID=40&md5=85437bd1e207346cee4a148ec83cf355

The issue of graduates' employability has become a major concern in many countries as the number of graduates keep increasing over the years. Fresh graduates are experiencing difficulties in finding meaningful employment as the growth in hiring has slowed in the recent period. With the impact of fourth industrial revolution, today graduates face a world transformed by technology. The role of universities in higher education become more challenging in shaping more digital technology graduates with the right skills and knowledge. Problems can be seen at both management level of higher education in producing graduates who can meet the needs of industry while industry is also facing the problem of finding skilled graduates who suit their needs. To examine the work skills demanded from Industry of Malaysian, this study proposed a text mining approach from 465 unstructured data of analyst job vacancies in classifying job titles and extracting vacancy and skills from job descriptions. The methodology involved are text retrieval, text pre-processing, word cloud corpus generation and text clustering. The findings indicate that the selected job posts emphasize more on vacancies information rather than skills needed which further shows the gap existence between the skills demand and supply. © 2020 Published under licence by IOP Publishing Ltd.