Applicable Authorship Verification
Table 4. Evaluation results for the test corpus CReddit.
['[BOLD] AV Method', '[BOLD] c@1', '[BOLD] AUC', '[BOLD] TP', '[BOLD] FN', '[BOLD] FP', '[BOLD] TN', '[BOLD] UP']
In the following we show to which extent these assumptions hold. All examined AV methods (with no exception) are fooled by the topical bias in the corpus. Here, the highest achieved results in terms of c@1 and AUC are very close to random guessing. A closer look at the confusion matrix outcomes reveals that some methods, for example ImpGI and OCCAV, perform almost entirely inverse to each other, where the former predicts nothing but Y and the latter nothing but N (except 1 Y). Moreover, we can assume that the lower c@1 is, the stronger is the focus of the respective AV method on the topic of the documents. Overall, the results of this experiment suggest that none of the examined AV methods is robust against topical influence.