An Empirical Study of Offensive Language in Online Interactions (Rochester Institute of Technology)

“Content moderators often have to deal with lengthy texts without any word-level indicators. We propose a neural transformer approach for detecting the tokens that make a particular post aggressive. The pre-trained BERT model has achieved state-of-the-art results in various natural language processing tasks. However, the model is trained on general-purpose corpora and lacks aggressive social media linguistic features. We propose fBERT, a retrained BERT model with over 1.4 million offensive tweets from the SOLID dataset.”

https://scholarworks.rit.edu/cgi/viewcontent.cgi?article=11933&context=theses