Detecting Offensive Language in TweetsUsing Deep Learning
Table 4: Detailed Results for every Class Label
['[BOLD] Proposed  [BOLD] Approach', '[BOLD] Class', '[BOLD] Precision', '[BOLD] Recall', '[BOLD] F-Score']
Results by other researchers have not been included, as these figures are not reported in the existing literature. As can be seen, sexism is quite easy to classify in hate-speech, while racism seems to be harder; similar results were reported by Davidson et al. This result is consistent across all ensembles.