Click it or Leave it: Detecting and Spoiling Clickbait with Informativeness Measures and Large Language Models

Ali Nemati6 days ago23 sec read15 views

Researchers introduced a hybrid method for detecting clickbait that combines transformer-based text embeddings with linguistic features, achieving an F1-score of 91% using XGBoost. This approach enhances transparency by identifying key linguistic cues and offers tools to support further research, helping content creators combat the spread of misleading headlines online.

Read the full article at arXiv cs.CL (NLP)

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Click it or Leave it: Detecting and Spoiling Clickbait with Informativeness Measures and Large Language Models

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