On the Challenges of Detecting Rude Conversational Behaviour
Table 3: Accuracies from training different models to classify each time frame into one of three classes of rudeness or none.
['SVM kernel', 'Accuracy (%) All Classes', 'Accuracy (%) Rude Classes']
Any arbitrary classifier can achieve an accuracy of approximately 70% by trivially predicting that the user is not being rude at each moment during a one-on-one interaction. This is because in most conversations where the user engages in some kind of rude conversational behaviour, roughly less than one-third of time frames consist of rudeness. However, a more interesting and relevant question for our task is how well the same model performs on detecting instances of rudeness. Surprisingly, each model’s ability to correctly identify instances of rudeness is quite poor compared to its overall accuracy. The top-performing model on rudeness classes achieves just 26.4% accuracy.