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arXiv · 2412.10576

Agro-STAY : Collecte de données et analyse des informations en agriculture alternative issues de YouTube

Laura Maxim·Julien Rabatel·Jean-Marc Douguet·Natalia Grabar·Roberto Interdonato·Sébastien Loustau·Mathieu Roche·Maguelonne Teisseire
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Abstract

To address the current crises (climatic, social, economic), the self-sufficiency -- a set of practices that combine energy sobriety, self-production of food and energy, and self-construction - arouses an increasing interest. The CNRS STAY project (Savoirs Techniques pour l'Auto-suffisance, sur YouTube) explores this topic by analyzing techniques shared on YouTube. We present Agro-STAY, a platform designed for the collection, processing, and visualization of data from YouTube videos and their comments. We use Natural Language Processing (NLP) techniques and language models, which enable a fine-grained analysis of alternative agricultural practice described online. -- Face aux crises actuelles (climatiques, sociales, économiques), l'auto-suffisance -- ensemble de pratiques combinant sobriété énergétique, autoproduction alimentaire et énergétique et autoconstruction - suscite un intérêt croissant. Le projet CNRS STAY (Savoirs Techniques pour l'Auto-suffisance, sur YouTube) s'inscrit dans ce domaine en analysant les savoirs techniques diffusés sur YouTube. Nous présentons Agro-STAY, une plateforme dédiée à la collecte, au traitement et à la visualisation de données issues de vidéos YouTube et de leurs commentaires. En mobilisant des techniques de traitement automatique des langues (TAL) et des modèles de langues, ce travail permet une analyse fine des pratiques agricoles alternatives décrites en ligne.

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Laura Maxim, Julien Rabatel, Jean-Marc Douguet, Natalia Grabar, Roberto Interdonato, Sébastien Loustau, Mathieu Roche, Maguelonne Teisseire. 2024-12-13. Agro-STAY : Collecte de données et analyse des informations en agriculture alternative issues de YouTube. https://arxiv.org/abs/2412.10576

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