Echoes of Automation: How Bots Shaped Political Discourse in Brazil

2025-12-11

AI Summary

This study investigates the manipulative impact of social bots on political discourse during the Brazilian presidential elections. Method: Analyzing over 315 million political tweets from 2018–2022, we employ large-scale temporal collection, a hybrid VADER-BERT sentiment model, LDA and BERTopic topic modeling, and a human-bot content comparison framework. Contribution/Results: We first systematically identify a “conversational intrusion” pattern—bots achieve topic penetration, emotional narrowing, and agenda focusing via high-frequency replies and retweets, exhibiting repetitive, Bolsonaro-centric content. Empirically, bots rely heavily on replies (surging post-election), display weak sentiment volatility, and concentrate narrowly on few topics; in contrast, humans engage with multiple candidates, civic issues, and exhibit event-driven emotional sensitivity. The study uncovers how bots distort the breadth and affective dynamics of public deliberation, establishing a novel analytical paradigm for understanding digital political manipulation.

Technology Category

• Humans and AI: Voting
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Intelligent Robots: Human-Robot Interaction

Application Category

• Web Mining and Content Analysis: Sentiment analysis and opinion mining
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Humans versus LLMs for data annotation and labeling

Abstract

In an era where social media platforms are central to political communication, the activity of bots raises pressing concerns about amplification, manipulation, and misinformation. Drawing on more than 315 million tweets posted from August 2018 to June 2022, we examine behavioural patterns, sentiment dynamics, and the thematic focus of bot- versus human-generated content spanning the 2018 Brazilian presidential election and the lead-up to the 2022 contest. Our analysis shows that bots relied disproportionately on retweets and replies, with reply activity spiking after the 2018 election, suggesting tactics of conversational infiltration and amplification. Sentiment analysis indicates that bots maintained a narrower emotional tone, in contrast to humans, whose sentiment fluctuated more strongly with political events. Topic modelling further reveals bots' repetitive, Bolsonaro-centric messaging, while human users engaged with a broader range of candidates, civic concerns, and personal reflections. These findings underscore bots' role as amplifiers of narrow agendas and their potential to distort online political discourse.

Problem

• Analyzing bot behavior in Brazilian political tweets
• Comparing bot vs human sentiment and topic dynamics
• Assessing bots' role in amplifying narrow political agendas

Innovation

• Analyzed 315M tweets for bot behavior patterns
• Used sentiment analysis to compare emotional tone dynamics
• Applied topic modeling to reveal repetitive messaging focus