Analyzing Toxicity in Social Media Discourse Around Wearing Face Masks During the COVID-19 Pandemic

Abstract

Toxicity in social media discourse around public issues is a fascinating area of research with real-world implications. When toxicity is left unchecked, it can result in devastating consequences to civil discourse and interpersonal relations online and offline. The debate around the use of face masks during the COVID-19 pandemic and the use of anti- and pro-face mask sentiment hashtags on Twitter presented an opportunity to study toxicity in social media discourse. This case study shows one way to analyze toxicity in social media discourse that is accessible to students and researchers with no prior computer programming skills. Several tools were used in conducting this research: Netlytic, a web-based software that enables live data collection from Twitter every 15 min, and Communalytic, a web-based software to conduct toxicity analysis using the Perspective API. The case study provides detailed steps for students and researchers interested in doing this kind of research, as well as some practical and ethical considerations for future studies.

Pascual-Ferrá, P., Alperstein, N., Barnett, D. J., & Rimal, R. N. (2021). Toxicity and verbal aggression on social media: Polarized discourse on wearing face masks during the COVID-19 pandemic. Big Data & Society. https://doi.org/10.1177/20539517211023533

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