Abstract
In recent years, many people on the internet write and post abusive language on online social media platforms such as Twitter, Facebook, etc. Detection of hate speech is very difficult to solve manually, especially in social media. Thus, we need to be automatic detection of hate speech in social media. We have used a benchmark dataset of approximately 25 thousand annotated tweets and proposed a model based on deep learning methods. We also compare the performance of our deep learning methods to the traditional machine learning classifier in terms of F1 Score and Accuracy. The results obtained through the proposed method is very promising.
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