Verbal aggression detection on Twitter comments: convolutional neural network for short-text sentiment analysis

Cyberbullying and hate speeches are common issues in online etiquette. To tackle this highly concerned problem, we propose a text classification model based on convolutional neural networks for the de facto verbal aggression dataset built in our previous work and observe significant improvement, thanks to the proposed 2D TF-IDF features instead of pretrained methods. Experiments are conducted to demonstrate that the proposed system outperforms our previous methods and other existing methods. A case study of word vectors is carried out to address the difficulty in using pre-trained word vectors for our short-text classification task, demonstrating the necessities of introducing 2D TF-IDF features. Furthermore, we also conduct visual analysis on the convolutional and pooling layers of the convolutional neural networks trained.