Unified Metadata-Aware Transformer Framework for Misleading News Classification
This research introduces MetaRoBERTa, a unified transformer-based representation learning framework, as a robust solution for multiclass misleading news classification, and integrates claims, contextual information, justification text, and speaker-related credibility metadata into a single textual representation.