Occupation similarity through bipartite graphs

TL;DR

This paper evaluates multiple explainable occupation similarity measures derived from bipartite graphs, demonstrating their ability to reveal diverse career paths using extensive Slovenian job transition data.

Contribution

It introduces and assesses various occupation similarity measures based on bipartite graphs, highlighting their different insights into inter-occupation relationships.

Findings

Multiple plausible similarity measures identified

Different measures suggest diverse career pathways

Framework validated on large-scale Slovenian data

Abstract

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.