Characterization of Political Polarized Users Attacked by Language Toxicity on Twitter

TL;DR

This study analyzes over 500 million Twitter posts to explore how political users experience language toxicity, revealing that Left users are more frequently targeted with toxic replies than Right or Center users.

Contribution

It provides the first large-scale analysis of toxicity flow among political groups on Twitter, highlighting differential attack patterns across political orientations.

Findings

Left users receive more toxic replies than others

Toxicity dynamics vary across political groups

Large-scale Twitter data used for analysis

Abstract

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.