We Can Detect Your Bias: Predicting the Political Ideology of News Articles

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We explore the task of predicting the leading political ideology or bias of news articles.

• First, we collect and release a large dataset of 34,737 articles that were manually annotated for political ideology -left, center, or right-, which is well-balanced across both topics and media.
• We further use a challenging experimental setup where the test examples come from media that were not seen during training, which prevents the model from learning to detect the source of the target news article instead of predicting its political ideology.
• From a modeling perspective, we propose an adversarial media adaptation, as well as a specially adapted triplet loss.