Un discours et un public "Gilets Jaunes" au coeur du Grand Débat National? Combinaison des approches IA et textométriques pour l'analyse de discours des plateformes "Grand Débat National" et "Vrai débat"
This work addresses methodological challenges in analyzing public discourse for political sociology and data science researchers, but it appears incremental as it combines existing methods without claiming major breakthroughs.
The study analyzed statements from two civic tech platforms, 'Grand Débat National' and 'Vrai Débat', by combining traditional textometric methods with AI-based approaches to examine social properties of speakers and explore research questions at the intersection of political sociology and data science, but no concrete results or numbers were reported.
In this contribution, we propose to analyze the statements coming from two ''civic tech'' platforms-the governmental platform, ''Grand D{é}bat National'' and, its political and algorithmic response proposed by a Yellow Vest collective, ''Vrai D{é}bat''-, 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.