Bias Discovery in News Articles Using Word Vectors

Given the ongoing controversy over biased news, it would be useful to have a system that can detect the extent of bias in online news articles and indicate it to the user in real time. Here we measure bias in a given sentence or article as the word vector similarity with a corpus of biased words. We compute the word vector similarity of each of the sentences with the words taken from a Wikipedia Neutral Point of View (NPOV) corpus, measured using the word2vec tool, where our model is trained using Wikipedia articles. We then compute the bias score, which indicates how much that article uses biased words. This is implemented as a web browser extension, which queries an online server running our bias detection algorithm. Finally, we validate the accuracy of our bias detection by comparing bias rankings of a variety of articles from various sources. We get lower bias scores for Wikipedia articles than for news articles, which is lower than that for opinion articles.