Constructing an anti-Asian hate indicator for pandemic-related comments from mainstream media YouTube channels

Abstract

Anti-Asian racism, linked to COVID-19, has become a serious social problem in the USA and all over the world and even led to hate crime and violence. Even though the current anti-Asian hate study focuses anti-Asian hate classification using machine learning and sentiment analysis toward tweets, this study provides a novel pandemic-news-related anti-Asian hate indicator to depict the anti-Asian hate shift of YouTube mainstream media commentary section. A new dataset for daily hate signal generation, which contains over one million YouTube comments, has been generated in this study. To train the classifier, 3,759 comments are sampled and manually labelled as hate and non-hate. In the model selection among machine learning and deep learning algorithms, a CNN model is selected as the best one with a 95% accuracy and a 0.99 AUC score, which can classify 1,433,246 comments.