TikTok

Mechanism-oriented taxonomy of indirect linguistic encoding improves LLM-based coded language detection

Researchers propose a comprehensive taxonomy of indirect linguistic expressions (ILE) — covering algospeak, euphemisms, and adversarial obfuscation — organized by underlying encoding mechanisms rather than communicative intent. The taxonomy is evaluated by injecting it into LLM prompts and benchmarked against four existing taxonomies and a no-taxonomy baseline on 2,000 manually annotated TikTok and Bluesky posts. The proposed taxonomy achieves 4.7% accuracy and 5.4% F1 improvements over the best competing approach across three LLMs, suggesting structured linguistic scaffolding meaningfully aids content moderation tasks.