Computer Science – Social and Information Networks
Scientific paper
2012-02-23
Computer Science
Social and Information Networks
8 pages, 5 figures. arXiv admin note: significant text overlap with arXiv:1201.3783
Scientific paper
Like other social media websites, YouTube is not immune from the attention of spammers. In particular, evidence can be found of attempts to attract users to malicious third-party websites. As this type of spam is often associated with orchestrated campaigns, it has a discernible network signature, based on networks derived from comments posted by users to videos. In this paper, we examine examples of different YouTube spam campaigns of this nature, and use a feature selection process to identify network motifs that are characteristic of the corresponding campaign strategies. We demonstrate how these discriminating motifs can be used as part of a network motif profiling process that tracks the activity of spam user accounts over time, enabling the process to scale to larger networks.
Carthy Joe
Cunningham Padraig
Harrigan Martin
O'Callaghan Derek
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