Abusive Language Detection
Original paper - https://www.aclweb.org/anthology/N19-1221 Here is a quick summary: In the paper submitted by Facebook AI, London to the recent NAACL (North American Chapter of the Association for Computational Linguistics) conference held in Minneapolis, they presented a novel approach using Graph Convolutional Networks to outperform some the best ways to detect abusive language on the internet. The approach made use of a heterogeneous graph that contains an authors community network and tweets. The graph is then used to predict the class and generate an embedding. In the paper's experiments, the researchers used embeddings from node2vec (sample implementation here https://snap.stanford.edu/node2vec/) and a 2-layer Graph Convolutional Network. The Graph Convolutional Network that represents the author's profiles and tweets were used to predict the author's tweet into three classes using a softmax layer as the output layer of the network. To extract the embedding f