\csq@thequote@oinit\csq@thequote@oopenDid I Say Something Wrong?\csq@thequote@ocloseA Word-Level Analysis of Wikipedia Articles for Deletion Discussions
Table 2: This table shows the average performance of the classifiers with the various timeframes. The values are the arithmetic mean of the classifiers’ results. These are an SVM, a NB classifier and an LM classifier. A bold font highlights the best result considering this metric. The plus and minus symbols indicate whether the performance metric was calculated for disruptive (+) or constructive contributions (−).
['[BOLD] time', '[BOLD] recall+', '[BOLD] recall−', '[BOLD] precision+', '[BOLD] precision−', '[BOLD] F1+', '[BOLD] F1−', '[BOLD] accuracy', '[BOLD] AUC']
The figure shows how the values for all metrics peak at the 1 day timeframe and worsen the longer the timeframe becomes. The positive precision value is the only one which was not the highest using a 1 day timeframe. It was 49.81% for 13 hours and 49.29% for 1 day. Nevertheless, this is negligible considering that the 1 day timeframe resulted in the greatest positive F1 score and accuracy. Thus, successive tests were performed using 1 day as timeframe length.