Job description mining to understand undergraduate co-operative placements

Abstract

Co-operative education has become popular worldwide. In this thesis, we use a text mining methodology to analyze over 17,000 co-op job postings in order to understand the co-op market in a large post-secondary institution. First, we develop a parser that extracts informative terms from free text job descriptions. These terms include soft skills, technical skills as well as perks and indicators of company culture. Second, we group the job descriptions by discipline and academic year and analyze the differences between various segments of the co-op market. We obtain insight that can benefit students, employers and the institution.