Bots, Elections, and Controversies: Twitter Insights from Brazil's Polarised Elections

TL;DR

This study analyzes 437 million tweets from Brazilian politics during two election cycles, revealing escalating bot activity, suspicious account behaviors, and complex networks that impact political discourse and can inform improved detection methods.

Contribution

It provides a comprehensive analysis of bot behaviors, account creation patterns, and network structures during Brazil's polarized elections, offering new insights for bot detection and political influence studies.

Findings

Bot engagement increased during COVID-19 and post-2022 election.

High correlation between bot activity and reply volume ($r=0.66$, $p<0.01$).

Presence of suspicious activities like mass account creation and multi-handle usage.

Abstract

From 2018 to 2023, Brazil experienced its most fiercely contested elections in history, resulting in the election of far-right candidate Jair Bolsonaro followed by the left-wing, Lula da Silva. This period was marked by a murder attempt, a coup attempt, the pandemic, and a plethora of conspiracy theories and controversies. This paper analyses 437 million tweets originating from 13 million accounts associated with Brazilian politics during these two presidential election cycles. We focus on accounts' behavioural patterns. We noted a quasi-monotonic escalation in bot engagement, marked by notable surges both during COVID-19 and in the aftermath of the 2022 election. The data revealed a strong correlation between bot engagement and the number of replies during a single day ($r=0.66$, $p<0.01$). Furthermore, we identified a range of suspicious activities, including an unusually high number of accounts being created on the same day, with some days witnessing over 20,000 new accounts and super-prolific accounts generating close to 100,000 tweets. Lastly, we uncovered a sprawling network of accounts sharing Twitter handles, with a select few managing to utilise more than 100 distinct handles. This work can be instrumental in dismantling coordinated campaigns and offer valuable insights for the enhancement of bot detection algorithms.