Agro-STAY: Data collection and analysis of alternative agriculture practices from YouTube
Maxim L., Rabatel J., Douguet J.M., Grabar N., Interdonato R., Loustau S., Rajaonarivo L., Roche M., Teisseire M.. 2025. In : Idrissi Najlae (ed.), Hair Abdellatif (ed.), Lazaar Mohamed (ed.), Saadi Youssef (ed.), Chakib Houda (ed.), Erritali Mohammed (ed.), El Kafhali Said (ed.). Artificial intelligence and green computing: Proceedings of the 2nd International Conference on Artificial Intelligence and Green Computing ICAIGC 2025. Cham : Springer, p. 71-82. (Lecture Notes in Networks and Systems, 1589). International Conference on Artificial Intelligence and Green Computing (ICAIGC 2025). 2, 2025-05-14/2025-05-16, Beni Mellal (Maroc).
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, querying and visualization of data from YouTube videos and their comments. We propose a full methodology dedicated to processing YouTube videos, and apply Natural Language Processing (NLP) techniques and language models, which enable a fine-grained analysis of alternative agricultural practices described online. In addition, we provide a well-adapted graphical user interface to help the experts analyzing the extracted knowledge.
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Agents Cirad, auteurs de cette publication :
- Interdonato Roberto — Es / UMR TETIS
- Roche Mathieu — Es / UMR TETIS