Moreover, two graph convolutional networks are leveraged to learn the latent representations depicting how sessions interact with one another in terms of users, and how posts are correlated with each other in terms of words.
we address several challenges in this work: (a) how to perform explainable cyberbullying detection that can boost detection performance, (b) how to highlight explainable comments without the ground truth, (c) how to model the correlation between posted text and user comments, and (d) how to model the interactions between sessions in terms of users, and the interactions between textual posts in terms of words.