# Un discours et un public "Gilets Jaunes" au coeur du Grand D'ebat National? Combinaison des approches IA et textom'etriques pour l'analyse de discours des plateformes "Grand D'ebat National" et "Vrai d'ebat"

arXiv: https://arxiv.org/abs/2211.11521 · HTML: https://mlsanity.com/paper/2211.11521/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 17 references that are in the map.
- First posted on arXiv 14 Nov 2022.

## Builds on (most cited first, 3 of 3)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [CamemBERT: a Tasty French Language Model](https://mlsanity.com/paper/1911.03894/) (2019)

## Abstract (arXiv)

In this contribution, we propose to analyze the statements coming from two ''civic tech'' platforms-the governmental platform, ''Grand D'ebat National'' and, its political and algorithmic response proposed by a Yellow Vest collective, ''Vrai D'ebat''-, by confronting two families of algorithms dedicated to text analysis. We propose to implement, on the one hand, proven approaches in textual data analysis (Reinert/Iramuteq Method) which have recently shown their interest in the analysis of very large corpora and, on the other hand, new methods resulting from the crossroads of the computer worlds, artificial intelligence and automatic language processing. We will examine the methodological solutions for qualifying the social properties of speakers about whom we have little direct information. Finally, we will attempt to present some research questions at the crossroads of the political sociology of public opinion and data science, which such a confrontation opens up.