Identifying Threats on Social Media to Spot Offensive Behavior

In the modern age, with the help of social media, communication has become available for everyone. Offensive text is broadly used in social media to humiliate or threaten someone. Offensive text like a bully, trolling, threats, and sexual harassment are used to demotivate someone. We have gathered a dataset of 44,000 comments from social media. We use five different models: DistilBERT, Multilingual BERT, XLM-RoBERTa-base, XLM-RoBERTa-large, and BanglaBERT. Variations in various parameters, e.g., learning rate, dropout rate, training epoch, early stopping, and batch size, are made to get better results. From our proposed model, the XLM-RoBERTa-base shows the highest accuracy, 83.54%, whereas m-BERT provides the highest AUC value of 0.85.