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Nowadays, bots that seek to manipulate political processes are omnipresent in online social
networks. However, we still know very little about their actual influence on people’s political
opinions and behaviour. We integrate insights from political communication theories with opinion
dynamics models to study the influential effects of bots at the individual and group levels. In an experimental pre-post design setting, LLM-based chatbots discuss political issues with human participants. By comparing the opinions of the participants before and after the discussion, we assess the treatment effect of the chatbots. The bots are programmed to apply a selection of communicative persuasion tactics such as repetition, critical mass, homophily, and message personalisation, to allow for nuanced insights on the varying effects of the aforementioned tactics. This study uncovers the causal mechanisms through which bots are influencing political opinion formation online and provides a comprehensive framework that allows us to understand the consequences of political decision-making in the digital era.