Classifying Tweet Level Judgements of Rumours in Social Media
Table 2: Accuracy taken across all rumours in the LOO setting.
['method', 'acc']
ICM can not use correlations to target rumour in this case and so can not be used. The majority baseline simply assigns the most frequent class from the training set. Most notably, performance increases from 70% to around 80%, after only 10 annotated tweets from However, as the amount of target rumour increases, performance does not increase further, which suggests that even only 10 human-annotated tweets are enough to achieve significant performance benefits. Note also how the use of reference rumours is very important, as methods using only the target rumour obtain accuracy similar to the Majority vote classifier (GP Brown and GP BOW).