Researchers have developed a multi-stage framework to detect reclaimed slurs in multilingual social media, focusing on LGBTQ+-related terms in English, Spanish, and Italian. The approach tackles data scarcity and class imbalance by integrating data-driven model selection, semantic-preserving augmentation via back-translation, and inductive transfer learning with dynamic undersampling. Language-specific threshold optimization improved the F1 score by 2-5% without retraining, highlighting significant cross-linguistic variations in sentiment expression and slur usage. AI
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IMPACT Enhances NLP capabilities for analyzing sensitive language across diverse linguistic contexts.
RANK_REASON Academic paper on a novel methodology for NLP task. [lever_c_demoted from research: ic=1 ai=1.0]