Detecting conspiracy theories requires understanding speaker intent through social context, not just analyzing text—and AI agents that adaptively query relevant context perform better than models that process all context at once.
This paper tackles conspiracy detection on social media by recognizing that the same text can express endorsement, criticism, or satire depending on context and speaker intent. The authors propose an agentic framework with tools for querying social context (like user history and network information) to infer whether someone genuinely believes conspiracy theories or is being sarcastic.