A Large-Scale English Multi-Label Twitter Dataset for Cyberbullying and Online Abuse Detection

Abstract

In this paper, we introduce a new English Twitter-based dataset for online abuse and cyberbullying detection. Comprising 62,587 tweets, this dataset was sourced from Twitter using specific query terms designed to retrieve tweets with high probabilities of various forms of bullying and offensive content, including insult, profanity, sarcasm, threat, porn and exclusion. Analysis performed on the dataset confirmed common cyberbullying themes reported by other studies and revealed interesting relationships between the classes. The dataset was used to train a number of transformer-based deep learning models returning impressive results.