The rapid proliferation of news and posts across social media platforms has spawned a concerning wave of misinformation. Disseminating false information and news significantly threatens public health and safety. To address this critical issue, we present an innovative disinformation detection framework, leveraging the power of multi-task learning (MTL) and meta-heuristic techniques. Our framework harnesses the potential of an MTL approach and a state-of-the-art pre-trained Transformer-based model, enabling the extraction of comprehensive contextual features from Arabic social media posts. These contextual are input to an advanced feature selection (FS) model utilizing a modified Nutcracker Optimization Algorithm. Through extensive evaluation of diverse datasets of Arabic social media posts, our proposed framework achieves remarkable results. Notably, our framework attains an accuracy rate of 87% and …