Zombie Follower Recognition Based on Industrial Chain Feature Analysis

Zombie followers, a type of bot, are longstanding entities in Sina Weibo. Although the features and detection of zombie followers have been extensively studied, zombie followers are continuously increasing in social networks and gradually developing into a large-scale industry. In this study, we analyze the features of eight groups of zombie followers from different companies. The findings indicate that although zombie followers controlled by different companies vary greatly, some industries may be controlled by the same organization. Based on the feature analysis, we use multiple machine learning methods to detect zombie followers, and the results show that zombie follower groups with short registration time are more easily detected. The detection accuracy of zombie followers that have been cultivated for a long duration is low. Moreover, the richer the feature sets, the higher the recall, precision, and F1 of their detection results will be. Under a given rich feature set, the accuracy of the combined-group detection is not as high as that of the single-group detection. The random forest achieves the highest accuracy in both single- and combined-group detections, yielding 99.14% accuracy in the latter case.