NetSpam: a Network-based Spam Detection Framework for Reviews in Online Social Media
TABLE IV: Weights of all features (with 5% data as train set); features are ranked based on their overall average weights.
['Dataset - Weights', 'DEV', 'NR', 'ETF', 'BST', 'RES', 'PP1', 'ACS', 'MCS']
Features Weights Importance: Combination of these features can be a good hint for obtaining better performance. The results of the Main dataset show all the four behavioral features are ranked as first features in the final overall weights. In addition, as shown in the Review-based as well as other two datasets, DEV is the most weighted feature. This is also same for our second most weighted feature, NR. From the third feature to the last feature there are different order for the mentioned features. The third feature for both datasets User-based and Review-based is same, ETF, while for the other dataset, Item-based, PP1 is at rank 3.