A new research paper explores the challenges of interpreting harmful online communication, particularly within cybercrime communities on platforms like Discord. The study found that while local context aids interpretation, external knowledge and extended conversational context significantly improve human understanding. Large language models also benefit from local context, with larger models showing better performance. The research proposes treating harmful content analysis as an evidence-integration problem rather than simple message-level classification. AI
IMPACT Highlights the need for more sophisticated AI approaches to understand nuanced and coded language in online communication for safety applications.
RANK_REASON Academic paper published on arXiv detailing research findings. [lever_c_demoted from research: ic=1 ai=1.0]
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