Bots, Disinformation, and the First Trump Impeachment

TL;DR

This study analyzes Twitter bots during Trump's first impeachment, revealing their disproportionate role in spreading disinformation, especially within echo chambers like Qanon, and quantifies their influence on online discussions.

Contribution

It provides a large-scale empirical analysis of bot behavior, disinformation spread, and network influence during a major political event, highlighting the structure and impact of different bot groups.

Findings

Bots generate over 31% of impeachment tweets despite being 1% of users.

Qanon bots constitute about 10% of supporters and form hierarchical networks.

Pro-Trump and anti-Trump bots have similar influence per bot, Qanon bots less so.

Abstract

Automated social media accounts, known as bots, have been shown to spread disinformation and manipulate online discussions. We study the behavior of retweet bots on Twitter during the first impeachment of U.S. President Donald Trump. We collect over 67.7 million impeachment related tweets from 3.6 million users, along with their 53.6 million edge follower network. We find although bots represent 1% of all users, they generate over 31% of all impeachment related tweets. We also find bots share more disinformation, but use less toxic language than other users. Among supporters of the Qanon conspiracy theory, a popular disinformation campaign, bots have a prevalence near 10%. The follower network of Qanon supporters exhibits a hierarchical structure, with bots acting as central hubs surrounded by isolated humans. We quantify bot impact using the generalized harmonic influence centrality measure. We find there are a greater number of pro-Trump bots, but on a per bot basis, anti-Trump and pro-Trump bots have similar impact, while Qanon bots have less impact. This lower impact is due to the homophily of the Qanon follower network, suggesting this disinformation is spread mostly within online echo-chambers.