Agentic Detection of Online Conspiracies
Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express endorsement, legitimate concerns, criticism, satire, or mockery. The main challenge is therefore not only recognizing conspiracy-related claims, but inferring the speaker's intent -- the utterance's illocutionary force. We argu
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Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express endorsement, legitimate concerns, criticism, satire, or mockery. The main challenge is therefore not only recognizing conspiracy-related claims, but inferring the speaker's intent -- the utterance's illocutionary force. We argu
This paper introduces an agentic framework for detecting online conspiracies by inferring speaker intent, which is a critical challenge in content moderation and combating misinformation. For ML engineers, understanding how to build systems that can interpret nuanced social contexts and 'illocutionary force' is becoming increasingly important for robust AI applications.