Occupation similarity through bipartite graphs
This work addresses the need for diverse occupation similarity measures to aid career decision-making, though it is incremental as it applies existing graph methods to a specific domain.
The study tackled the problem of measuring occupation similarity for career decisions by proposing multiple explainable measures derived from bipartite graphs, and validated them on over 450,000 job transitions in Slovenia from 2012 to 2021, showing that several measures are plausible and offer different career paths.
Similarity between occupations is a crucial piece of information when making career decisions. However, the notion of a single and unified occupation similarity measure is more of a limitation than an asset. The goal of the study is to assess multiple explainable occupation similarity measures that can provide different insights into inter-occupation relations. Several such measures are derived using the framework of bipartite graphs. Their viability is assessed on more than 450,000 job transitions occurring in Slovenia in the period between 2012 and 2021. The results support the hypothesis that several similarity measures are plausible and that they present different feasible career paths. The complete implementation and part of the datasets are available at https://repo.ijs.si/pboskoski/bipartite_job_similarity_code.