D\'eveloppement automatique de lexiques pour les concepts \'emergents : une exploration m\'ethodologique

TL;DR

This paper introduces a four-step methodology combining human expertise, statistical analysis, and machine learning to automatically develop lexicons for emerging concepts, especially in non-technological innovation, demonstrating robustness and adaptability across domains.

Contribution

It presents a novel, generalizable methodology for automatic lexicon development for emerging concepts using a multi-step process integrating multiple techniques.

Findings

Robustness and relevance of the approach demonstrated

Methodology adaptable to various contexts

Effective identification of new terms in conceptual fields

Abstract

This paper presents the development of a lexicon centered on emerging concepts, focusing on non-technological innovation. It introduces a four-step methodology that combines human expertise, statistical analysis, and machine learning techniques to establish a model that can be generalized across multiple domains. This process includes the creation of a thematic corpus, the development of a Gold Standard Lexicon, annotation and preparation of a training corpus, and finally, the implementation of learning models to identify new terms. The results demonstrate the robustness and relevance of our approach, highlighting its adaptability to various contexts and its contribution to lexical research. The developed methodology promises applicability in conceptual fields.