\csq@thequote@oinit\csq@thequote@oopenDid I Say Something Wrong?\csq@thequote@ocloseA Word-Level Analysis of Wikipedia Articles for Deletion Discussions
Table 6: This table shows the performance of the SVM and NB classifier using the sliding window approach with stratified sampling. Function words classifications are marked with “FW”. All others were full text classifications. The plus and minus symbols indicate whether the performance metric was calculated for disruptive (+) or constructive contributions (−).
['[BOLD] Classifier', '[BOLD] Recall+', '[BOLD] Recall−', '[BOLD] Precision+', '[BOLD] Precision−', '[BOLD] F1+', '[BOLD] F1−', '[BOLD] Accuracy', '[BOLD] AUC']
This bar chart shows the performance of the full text SVM in contrast to it only factoring in function words. The classifier used the sliding window approach with stratified sampling. Thus, it erroneously performed well. The values are in relation to a random classifier with 0% expressing equal performance. The percentages refer to the overall performance, meaning that 50% equates to a perfect result.