Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Integrating textual data for enhanced explanation of food crises at subnational scale

Domaine:

socioeconomicnatural language processing

Type de record:

paperdataset
Créateur:
ValMenIntRoc
Éditeur:
TerStrNarPel
Éditeur:
CCSDCEU
Hôte:avatar
Source Agritrop Cirad (agritrop.cirad.fr) International audience In an attempt to anticipate Food Security (FS) crises and overcome the limits of existing early warning systems, predictive models can forecast risk indices by combining heterogeneous data. While using different data sources (e.g., satellite imagery, agroclimatic data, food prices) allows to consider various factors that may impact food crises, the explainability of these models remains challenging. In this work, we propose a Food Security indicator solely based on textual data, discerning among different triggers and accounting for possible biases in the spatial coverage of news. We evaluate our approach on a corpus of French-language documents from Burkina Faso and highlight its significance, paving the way for more open and explainable data sources for monitoring food insecurity.

Visit

hal.science

Tasks

text classification

Tags

Text MiningFood SecurityWest AfricaNatural Language Processing[SDV]Life Sciences [q-bio]

Licenses

https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/OpenAccess

Similaires

Deep learning models for enhanced forest-fire prediction at Mount Kilimanjaro, Tanzania: Integrating satellite images, weather data and human activities dataAlert at Maradi: Preventing Food Crises by Using Price SignalsDataset for Siswati: Parallel textual data for English and Siswati and monolingual textual data for SiswatiPredictive Cultivation: Integrating Meteorological Data and Machine Learning for Enhanced Crop Yield ForecastIntegrating big data into sustainable supply chain management: a pathway to enhanced firm performance in Ghana's food and beverage sectorReplication Data for the paper "Predicting Food-Security Crises in the Horn of Africa Using Machine Learning"

Deep learning models for enhanced forest-fire prediction at Mount Kilimanjaro, Tanzania: Integrating satellite images, weather data and human activities data

Alert at Maradi: Preventing Food Crises by Using Price Signals

This paper aims at exploiting grain price data to detect the warning signs of looming

Dataset for Siswati: Parallel textual data for English and Siswati and monolingual textual data for Siswati

Predictive Cultivation: Integrating Meteorological Data and Machine Learning for Enhanced Crop Yield Forecast

Agriculture is a key component of Telangana’s economy, and greater performance in this sector is cru

Integrating big data into sustainable supply chain management: a pathway to enhanced firm performance in Ghana's food and beverage sector

Purpose The study examines how big data analytics moderate the relationship be

Replication Data for the paper "Predicting Food-Security Crises in the Horn of Africa Using Machine Learning"

This folder contains all input data necessary to run the machine learning model as describe