Medium Framing

Media framing analysis investigates how the presentation of information shapes public perception, focusing on identifying and classifying different perspectives within news articles and social media posts. Current research utilizes natural language processing techniques, including large language models and contrastive pre-training, to automatically detect frames from text and images, often employing multi-label classification and narrative analysis to capture nuanced framing strategies. This work is significant for understanding media bias, societal attitudes towards complex issues, and the influence of framing on public opinion, with applications in social science research, policy analysis, and computational journalism.