Author Profiling for Hate Speech Detection
(b) Sexism class
['[BOLD] Method', '[BOLD] p', '[BOLD] r', '[BOLD] f1']
As in the previous experiments, the scores are averaged over 10 folds of cv. Of particular interest are the scores for the sexism class where the f1 increases by over 10 points upon the addition of author profiling features. Upon analysis, we find that such a substantial increase in performance stems from the fact that many of the 527 unique authors of the sexist tweets are closely connected in the community graph. This allows for their penchant for sexism to be expressed in their respective author profiles.