A deep dive into the consistently toxic 1% of Twitter

TL;DR

This study analyzes 14 years of Twitter data to identify profiles that consistently post toxic content, revealing patterns of thematic narrowness, potential coordination, and bot-like behavior, contributing a large longitudinal dataset for research.

Contribution

It introduces a longitudinal analysis of consistently toxic profiles on Twitter, highlighting behavioral patterns and providing a substantial dataset for future research.

Findings

Consistently toxic profiles focus on narrow themes with low diversity.

These profiles exhibit thematic similarity and potential coordination.

They are likely to have bot-like characteristics and influence intentions.

Abstract

Misbehavior in online social networks (OSN) is an ever-growing phenomenon. The research to date tends to focus on the deployment of machine learning to identify and classify types of misbehavior such as bullying, aggression, and racism to name a few. The main goal of identification is to curb natural and mechanical misconduct and make OSNs a safer place for social discourse. Going beyond past works, we perform a longitudinal study of a large selection of Twitter profiles, which enables us to characterize profiles in terms of how consistently they post highly toxic content. Our data spans 14 years of tweets from 122K Twitter profiles and more than 293M tweets. From this data, we selected the most extreme profiles in terms of consistency of toxic content and examined their tweet texts, and the domains, hashtags, and URLs they shared. We found that these selected profiles keep to a narrow theme with lower diversity in hashtags, URLs, and domains, they are thematically similar to each other (in a coordinated manner, if not through intent), and have a high likelihood of bot-like behavior (likely to have progenitors with intentions to influence). Our work contributes a substantial and longitudinal online misbehavior dataset to the research community and establishes the consistency of a profile's toxic behavior as a useful factor when exploring misbehavior as potential accessories to influence operations on OSNs.