Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics

Abstract

Racism and physical attacks on Asian communities have spread in the U.S. and around the world. Xenophobia is a virus that may lead to an ongoing social problem in the post-pandemic era. Although existing studies have been done to classify anti-Asian haters, little is known on monitoring, tracking, and characterizing anti-Asian haters on social media platforms. In this chapter, a systematic examination of anti-Asian haters tracking and profiling methods is designed by using big data analytics with deep learning algorithms. Target haters are investigated and tracked by analyzing public opinions towards key topics in 2020, including the U.S. elections, stimulus checks, and economy opening strategies throughout data collection and preprocessing, text classification, sentiment analysis, data visualization, and association rule. Such a comprehensive study provides a variety of research opportunities in dealing with anti-Asian racism and xenophobia in and after the COVID-19 pandemic.