Before revision:  and Convolutional Neural Networks to detect depressed users on social media such as Twitter-based on multi-modal features . Specifically, we encode words in user posts using pre-trained word embeddings and BiGRUs to capture latent behavioural patterns, long-term dependencies, and correlation across the modalities, including semantic sequence features from the user timelines (posts).
After revision:  and Convolutional Neural Networks to detect depressed users on social media and explain the model prediction. We have considered user posts along with Twitter-based on multi-modal features . Specifically, we encode words in user posts using pre-trained word embeddings and BiGRUs to capture latent behavioural patterns, long-term dependencies, and correlation across the modalities, including semantic sequence features from the user timelines (posts).