AI and Emotional Polarization: Analysis of a Viral Video as a Narrative of Political Disinformation in Brazil
DOI:
https://doi.org/10.12795/Ambitos.2025.i68.01Keywords:
artificial intelligence, disinformation, political polarization, echo chambers, BrazilAbstract
This article examines how artificial intelligence and recommendation algorithms drive the circulation of polarized discourse, based on a reel published by Jair Bolsonaro on Facebook on September 13, 2024. By scraping and cleaning 1,500 user comments, a representative corpus of public interaction was constructed. The study employed a mixed-methods protocol combining data cleaning in Python, exploratory analysis using IRaMuTeQ, topic modeling through Latent Dirichlet Allocation (LDA), and co-occurrence matrices via Labbe’s method, ensuring reproducibility and transparency. The results reveal that religious symbols such as capeta and Deus, along with derogatory labels like nove dedos, reduce complex problems to binary moral frames. Word clouds and distance matrices confirm a strong association between demonizing references and attacks against Luiz Inácio Lula da Silva. Factorial analysis identifies five clearly segmented discursive clusters and visualizes thematic tensions between exaltation and delegitimization. Moreover, this combination of computational and qualitative methods offers a methodological advancement for future research on digital polarization. The implications of these findings may inform public policy makers and platform designers regarding concrete interventions to mitigate AI-driven disinformation. The study concludes that artificial intelligence functions as an engine of large-scale disinformation, reinforcing confirmation bias and undermining critical deliberation by prioritizing emotional framing over analytical reasoning. While the research is based on a single case with limited scope, its results open avenues for future comparative inquiry, particularly within Latin American contexts where the dynamics of digital polarization remain underexplored.
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