Title: Constructing an anti-Asian hate indicator for pandemic-related comments from mainstream media YouTube channels
Authors: Xin Wang; Xi Chen; Bodian Li; Peng Zhao
Addresses: Big Data and AI Lab, IntelligentRabbit LLC, NJ, USA ' School of Humanity and Law, Beijing University of Civil Engineering and Architecture, Beijing, China ' Northeastern University, Boston, USA ' Big Data and AI Lab, IntelligentRabbit LLC, NJ, USA
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.
Keywords: COVID-19; pandemic-related hate; anti-Asian hate indicator; mainstream media; big data analytics; machine learning; deep learning.
International Journal of Society Systems Science, 2021 Vol.13 No.4, pp.278 - 293
Received: 20 Feb 2021
Accepted: 06 Aug 2021
Published online: 18 Aug 2022 *