Methodology for Analyzing Educational Forums with NLP: Searching for Economic Terms

This record corresponds to the accepted manuscript (post-print) of a book chapter published in Teaching Innovations in Economics.

The chapter proposes a methodological framework for analyzing educational forums using Natural Language Processing (NLP) techniques to identify and study economic terminology. The approach follows the CRISP-DM methodology and integrates text preprocessing, frequency analysis, topic modeling, and sentiment analysis using Python libraries such as spaCy and transformer-based models. The results are communicated through visual analytics to support interpretation and educational decision-making.

The final published version is available at the publisher’s website:
https://doi.org/10.1007/978-3-031-72549-4_4

This deposit is made for dissemination and academic visibility purposes, in accordance with the publisher’s self-archiving policy.