Detecting Online Hate Speech Using Context Aware Models
Table 1: Performance of Logistic Regression Models
['[BOLD] Features', '[BOLD] Input Contents', '[BOLD] Accuracy', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F1', '[BOLD] AUC']
The result shows that the logistic regression model was improved in every metric after adding both word-level n-gram features and lexicon derived features. However, the improvements are moderate. It shows that in addition to character level features, adding more features can improve hate speech detection performance. However, the improvement is limited. Compared with baseline model, the F1 score only improves 1.3%.