Systematic LLM evaluation for news framing detection reveals prompt sensitivity and emotional-language bias, introduces an out-of-domain headline dataset, and shows cross-model consensus aids annotation auditing.
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2 Pith papers cite this work. Polarity classification is still indexing.
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LLMs show low endorsement of persuasion-infused messages unless given partisan personas, which then increase polarized endorsements varying by technique and topic.
citing papers explorer
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Political Persuasion and Endorsement in Large Language Models
LLMs show low endorsement of persuasion-infused messages unless given partisan personas, which then increase polarized endorsements varying by technique and topic.