In the Eyes of the Beholder: Analyzing Social Media Use of Neutral and Controversial Terms for COVID-19

TL;DR

This study analyzes social media usage of controversial versus neutral COVID-19 terms, revealing significant differences in topics and sentiment, and demonstrating that these terms are distinguishable through context analysis.

Contribution

It provides a quantitative analysis of the usage and implications of controversial COVID-19 terms using topic modeling, sentiment analysis, and classification with transformer models.

Findings

'Chinese Virus' is associated with different topics and sentiment than 'COVID-19'

The two terms are distinguishable by context using transformer-based classification

Controversial terms influence the framing and perception of COVID-19 discussions

Abstract

During the COVID-19 pandemic, "Chinese Virus" emerged as a controversial term for coronavirus. To some, it may seem like a neutral term referring to the physical origin of the virus. To many others, however, the term is in fact attaching ethnicity to the virus. While both arguments appear reasonable, quantitative analysis of the term's real-world usage is lacking to shed light on the issues behind the controversy. In this paper, we attempt to fill this gap. To model the substantive difference of tweets with controversial terms and those with non-controversial terms, we apply topic modeling and LIWC-based sentiment analysis. To test whether "Chinese Virus" and "COVID-19" are interchangeable, we formulate it as a classification task, mask out these terms, and classify them using the state-of-the-art transformer models. Our experiments consistently show that the term "Chinese Virus" is associated with different substantive topics and sentiment compared with "COVID-19" and that the two terms are easily distinguishable by looking at their context.