This paper presents the participation of IRISA to the task of fake news detection from tweets, relying either on the text or on propagation information. For the text based detection, variants of BERT-based classification are proposed. In order to improve this standard approach, we investigate the interest of augmenting the dataset by creating tweets with fine-tuned generative models. For the graph based detection, we have proposed models characterizing the propagation of the news or the users' reputation.