Analysis of the National Energy and Climate Plans of EU member states using Natural Language Processing (NLP)

Abstract

During recent years, Natural Language Processing (NLP) has experienced significant advancements thanks to the fast development of Deep-Learning models and text processing techniques. These advancements have revolutionized the way humans interact with machines, enabling a deeper and more contextual understanding. In this context, the present work focuses on leveraging this cutting-edge technology to analyse de National Energy and Climate Plans (NECP), documents where each European Union country outlines its roadmap to achieve a serie of objectives and measures by the year 2030. The analysis comprises, on the one hand, a bottom-up analysis where the main topics addressed in the European plans are identified, and on the other hand, a top-down analysis that classifies and assesses each country according to predefined discourses typologies. Once the analysis is completed, the strategies adopted by each country to meet European objectives are identified, and through and inductive approach, the coherence and accuracy of the algorithm developed are evaluated.