Characterization of Political Polarized Users Attacked by Language Toxicity on Twitter
This addresses the problem of understanding toxicity dynamics in political polarization on social media for researchers and policymakers, though it is incremental as it builds on prior large-scale data studies.
The study investigated language toxicity on Twitter during U.S. presidential elections, analyzing over 500M posts, and found that Left users received significantly more toxic replies than Right and Center users.
Understanding the dynamics of language toxicity on social media is important for us to investigate the propagation of misinformation and the development of echo chambers for political scenarios such as U.S. presidential elections. Recent research has used large-scale data to investigate the dynamics across social media platforms. However, research on the toxicity dynamics is not enough. This study aims to provide a first exploration of the potential language toxicity flow among Left, Right and Center users. Specifically, we aim to examine whether Left users were easier to be attacked by language toxicity. In this study, more than 500M Twitter posts were examined. It was discovered that Left users received much more toxic replies than Right and Center users.