Anti Vaccine

Anti-vaccine sentiment and misinformation pose a significant public health challenge, driving research focused on understanding and mitigating its spread. Current studies leverage natural language processing (NLP) techniques, including transformer-based models like BERT and DistilRoBERTa, and computer vision, to analyze social media data (e.g., Twitter, Instagram) for anti-vaccine content, sentiment, and associated misinformation. This research aims to identify patterns, influential actors, and effective counter-messaging strategies, ultimately informing public health interventions and improving the accuracy of automated detection systems. The insights gained are crucial for developing targeted communication campaigns and enhancing public trust in vaccines.