With the recent digitisation of vast text corpora and significant advancements in natural language processing, development economists can now address a wide range of novel research questions. This course begins with an introduction to collecting, processing, and representing numerically text data, followed by an exploration of specialised deep learning techniques to model the semantic and structural structures of language. The course prioritises intuitive understanding and practical implementation using Python. By the end of the course, students will be able to leverage a variety of data sources for empirical work, including documents, tweets, speeches, and news transcripts, for tasks such as topic modelling, sentiment analysis, document similarity, named entity recognition, and more.
- Enseignant éditeur: Chauvet Lisa
- Enseignant éditeur: Gorin Clement
