How can text mining improve the explainability of food security situations?

Deleglise Hugo, Bégué Agnès, Interdonato Roberto, Maître d'Hôtel Elodie, Roche Mathieu, Teisseire Maguelonne. 2023. How can text mining improve the explainability of food security situations?. Journal of Intelligent Information Systems, 24 p.

Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/IVVEQL / Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/C5PU01

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Psychologie-éthologie-ergonomie

Résumé : Food Security (FS) is a major concern in West Africa, particularly in Burkina Faso, which has been the epicenter of a humanitarian crisis since the beginning of this century. Early warning systems for FS and famines rely mainly on numerical data for their analyses, whereas textual data, which are more complex to process, are rarely used. However, this data is easy to access and represents a source of relevant information that is complementary to commonly used data sources. This study explores methods for obtaining the explanatory context associated with FS from textual data. Based on a corpus of local newspaper articles, we analyze FS over the last ten years in Burkina Faso. We propose an original and dedicated pipeline that combines different textual analysis approaches to obtain an explanatory model evaluated on real-world and large-scale data. The results of our analyses have proven how our approach provides significant results that offer distinct and complementary qualitative information on food security and its spatial and temporal characteristics.

Mots-clés Agrovoc : sécurité alimentaire, fouille de textes, analyse de données, journal, fouille de données

Mots-clés géographiques Agrovoc : Burkina Faso, Sahel

Mots-clés libres : Food Security, Sentiment analysis, Spatiotemporal analysis, Text Mining, Word embedding

Classification Agris : E10 - Économie et politique agricoles
C30 - Documentation et information
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 3 (2019-) - Systèmes alimentaires

Agences de financement hors UE : Agence Nationale de la Recherche

Projets sur financement : (FRA) Institut Convergences en Agriculture Numérique

Auteurs et affiliations

• Deleglise Hugo, Université de Grenoble (FRA) - auteur correspondant
• Bégué Agnès, CIRAD-ES-UMR TETIS (FRA)
• Interdonato Roberto, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0002-0536-6277 - auteur correspondant
• Maître d'Hôtel Elodie, CIRAD-ES-UMR MOISA (FRA)
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568
• Teisseire Maguelonne, INRAE (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/607743/)

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