Identifying News Broadcasters’ Ideological Perspectives Using a Large-Scale Video Ontology

Television news has been the predominant way of understanding the world around us, but individual news broadcasters can frame or mislead audience’s understanding about political and social issues. We aim to develop a computer system that can automatically identify highly biased television news, which may prompt audience to seek news stories from contrasting viewpoints. But can computers determine if news videos were produced by broadcasters holding differing ideological beliefs? We developed a method of identifying differing ideological perspectives based on a large-scale visual concept ontology, and the experimental results were promising.