The paper "CSI: A Hybrid Deep Model for Fake News Detection" addresses the challenging problem of detecting fake news, which has gained significant attention due to its potential to manipulate public opinion and elections. The authors propose a model called CSI, which combines three key characteristics of fake news: the text of an article, the user response it receives, and the source of the article. The model is composed of three modules: Capture, Score, and Integrate. The Capture module uses a Recurrent Neural Network (RNN) to capture the temporal pattern of user activity and textual content. The Score module learns the source characteristic based on user behavior. The Integrate module combines the outputs of the first two modules to classify articles as fake or not. Experimental results on real-world datasets demonstrate that CSI achieves higher accuracy than existing models and extracts meaningful latent representations of both users and articles. The CSI model is flexible, generalizes well, and does not require assumptions about the distribution of user behavior or the context of engagement.The paper "CSI: A Hybrid Deep Model for Fake News Detection" addresses the challenging problem of detecting fake news, which has gained significant attention due to its potential to manipulate public opinion and elections. The authors propose a model called CSI, which combines three key characteristics of fake news: the text of an article, the user response it receives, and the source of the article. The model is composed of three modules: Capture, Score, and Integrate. The Capture module uses a Recurrent Neural Network (RNN) to capture the temporal pattern of user activity and textual content. The Score module learns the source characteristic based on user behavior. The Integrate module combines the outputs of the first two modules to classify articles as fake or not. Experimental results on real-world datasets demonstrate that CSI achieves higher accuracy than existing models and extracts meaningful latent representations of both users and articles. The CSI model is flexible, generalizes well, and does not require assumptions about the distribution of user behavior or the context of engagement.