Misinformation poses a significant challenge, especially in developing countries with low literacy rates. The rapid spread on social media, coupled with their lack of robust verification mechanisms, makes distinguishing between credible and false information increasingly difficult. This document outlines our efforts to address this challenge in Burkina Faso using the pre-trained linguistic model CAMEMBERT. Our preliminary results show high performance (up to a 99.34% F1 score) on Fakipedia, suggesting that certain blatant instances of false information can be effectively identified and stopped by automated tools.

Fake News, Machine Learning, Text Classification, camemBERT, Artificial Intelligence