Identifying video spammers in online social networks
AIRWeb '08 Proceedings of the 4th international workshop on Adversarial information retrieval on the web
Uncovering social spammers: social honeypots + machine learning
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
Detecting and characterizing social spam campaigns
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Detecting spammers on social networks
Proceedings of the 26th Annual Computer Security Applications Conference
Who is tweeting on Twitter: human, bot, or cyborg?
Proceedings of the 26th Annual Computer Security Applications Conference
Design and Evaluation of a Real-Time URL Spam Filtering Service
SP '11 Proceedings of the 2011 IEEE Symposium on Security and Privacy
Suspended accounts in retrospect: an analysis of twitter spam
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Detecting collective attention spam
Proceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality
Spam filtering in twitter using sender-receiver relationship
RAID'11 Proceedings of the 14th international conference on Recent Advances in Intrusion Detection
Die free or live hard? empirical evaluation and new design for fighting evolving twitter spammers
RAID'11 Proceedings of the 14th international conference on Recent Advances in Intrusion Detection
Understanding and combating link farming in the twitter social network
Proceedings of the 21st international conference on World Wide Web
Proceedings of the 21st international conference on World Wide Web
Poultry markets: on the underground economy of twitter followers
Proceedings of the 2012 ACM workshop on Workshop on online social networks
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Online social networks, such as Twitter, have soared in popularity and in turn have become attractive targets of spam. In fact, spammers have evolved their strategies to stay ahead of Twitter's anti-spam measures in this short period of time. In this paper, we investigate the strategies Twitter spammers employ to reach relevant target audiences. Due to their targeted approaches to send spam, we see evidence of a large number of the spam accounts forming relationships with other Twitter users, thereby becoming deeply embedded in the social network. We analyze nearly 20 million tweets from about 7 million Twitter accounts over a period of five days. We identify a set of 14,230 spam accounts that manage to live longer than the other 73% of other spam accounts in our data set. We characterize their behavior, types of tweets they use, and how they target their audience. We find that though spam campaigns changed little from a recent work by Thomas et al., spammer strategies evolved much in the same short time span, causing us to sometimes find contradictory spammer behavior from what was noted in Thomas et al.'s work. Specifically, we identify four major strategies used by 2/3rd of the spammers in our data. The most popular of these was one where spammers targeted their own followers. The availability of various kinds of services that help garner followers only increases the popularity of this strategy. The evolution in spammer strategies we observed in our work suggests that studies like ours should be undertaken frequently to keep up with spammer evolution.