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arXiv · 2509.19890

DSA, AIA, and LLMs: Approaches to conceptualizing and auditing moderation in LLM-based chatbots across languages and interfaces in the electoral contexts

Natalia Stanusch·Raziye Buse Cetin·Salvatore Romano·Miazia Schueler·Meret Baumgartner·Bastian August·Alexandra Rosca
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Abstract

The integration of Large Language Models (LLMs) into chatbot-like search engines poses new challenges for governing, assessing, and scrutinizing the content output by these online entities, especially in light of the Digital Service Act (DSA). In what follows, we first survey the regulation landscape in which we can situate LLM-based chatbots and the notion of moderation. Second, we outline the methodological approaches to our study: a mixed-methods audit across chatbots, languages, and elections. We investigated Copilot, ChatGPT, and Gemini across ten languages in the context of the 2024 European Parliamentary Election and the 2024 US Presidential Election. Despite the uncertainty in regulatory frameworks, we propose a set of solutions on how to situate, study, and evaluate chatbot moderation.

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Natalia Stanusch, Raziye Buse Cetin, Salvatore Romano, Miazia Schueler, Meret Baumgartner, Bastian August, Alexandra Rosca. 2025-09-24. DSA, AIA, and LLMs: Approaches to conceptualizing and auditing moderation in LLM-based chatbots across languages and interfaces in the electoral contexts. https://arxiv.org/abs/2509.19890

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