NLP for Social Sciences

20

Français

Université Paris dauphine

The aim of the course is to provide theoretical and practical training in modern NLP methods for research in the social sciences (Economics, Management, Sociology, etc.). It is intended for students in the process of completing their thesis or for master's students who are considering pursuing a doctorate and adopting these rapidly developing methods. It's taught in French and English. Mainly with r but also with python.

Session 1 : Introduction - Tokenize and annotate corpus;
Session 2 : Semantic spaces and cooccurence analysis;
Session 3 : Topic modeling : from LDA to STM;
Session 4 : Embeddings : from Word2tex to Zero-shot-learning;
Session 5 : ML for text : sentiment, intention, emotion and others criteria.
Session 7, 8, 9 : hackathon (data set as to be defined - probably a large set of TV ads scripts);
Session 10 : students presentations;
The lecture will be delivery principally in r, but the parallel procedure with python will be also studied. All materials (script, data and references) will be available at ;
https://github.com/BenaventC/NLP_lecture_PSLWeek;

Participation to the hackathon and project presentation.

A basic knowledge of r/python is recommended.

BENAVENT Christophe

Bruno Chavez, José Carlos Romero Moreno, Olivier Caron, and Christophe Benavent from Acss Institute and DRM. Paris Dauphine-PSL;