Unveil the Spams in Weibo

In online social network(OSN), spams refer to the messages deliberately propagated by spammers. Annoyed advertisements, illegal contents, malware and phishing links can all be spread by spams. Some detection approaches have been proposed in previous works. However, on the one hand, some of the assumptions they rely on are still unproven. On the other hand, most of the previous works focus on famous sites such as Twitter and Facebook. The effectiveness of these approaches on other networks is still unknown. In this paper, we study the problem of spam in Weibo, Chinas leading micro-blog service. With a dataset of 375, 430 posts and 2, 370 users crawled from Weibo, we conducted a deep analysis in spammers and spammed posts. The contributions of our work are as follows. First, we work on the unproven assumption of regarding spammers as botnet users, which is relied by many previous works. We find that nowadays spammers perform more like regular users, which indicates that some previous methods are not effective any more. Second, we investigate the burst properties in spammed posts and legitimate posts. We find that there´re some useful features can be extracted to separate them. Finally, we provide some helpful features that are suitable for spam detection in Weibo.