A Stylometric Inquiry into Hyperpartisan and Fake News
Table 3: Accuracies, class-wise precision, recall, and F-Measure of predicting hyperpartisanship. Including baselines predicting all articles as hyperpartisan or mainstream, respectively
['[BOLD] Features', '[BOLD] Accuracy all', '[BOLD] Precision hyp.', '[BOLD] Precision main.', '[BOLD] Recall hyp.', '[BOLD] Recall main.', '[BOLD] F [BOLD] 1 hyp.', '[BOLD] F [BOLD] 1 main.']
The best classification accuracy of 0.75 at a remarkable 0.89 recall for the hyperpartisan class is achieved by the style-based classifier, outperforming the topic feature model.