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JTML at SemEval-2019 task 6: Offensive tweets identification using convolutional neural networks

Abstract:

In this paper, we propose the use of a Convolutional Neural Network (CNN) to identify offensive tweets. We use an end-to-end model (i.e., no preprocessing) and fine-tune pre-trained embeddings (FastText) during training for learning words' representation. We compare the proposed CNN model to a baseline model, such as Linear Regression, and several neural models. The results show that CNN outperforms other models, and stands as a simple but strong baseline in comparison to other systems submitted to the Shared Task.