• text mining
• circular economy topics
• topic modeling
• automatic extraction
• skill
• green professional profile
• circular economy

The Circular Economy (CE) is by now a highly treated topic both academically and in public debates. CE paradigm aims to obtain systems oriented towards not using the Earth depleting resources and to ensure that the flows of material and energy continuously re-enter the system in order to minimise waste.

There are several obstacles in the practical application of CE; among them the lack of a clear and widely accepted classification of CE related topics and the uncertainly of which skills and job profiles will be impacted by the new paradigm. Although, there are several databases of professional profiles, there is not a European agreement of which profiles are to be considered green.

In this thesis I faced the problem described above using automatic text analysis tools, achieving two outcomes: firstly, starting from scientific publications, I obtained a subdivision of CE into sub-topics; secondly, by crossing the topics and the European database of skills and profiles (ESCO), I extracted what can be considered job profiles related to CE, giving a useful tool to companies that want to adapt to the new paradigm.