Identifying web spam with user behavior analysis
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In this paper, we provide a high level overview of Spam 2.0, how it works, its impacts and its categorizations (which are annoying, tricky, deceiving and evil). We also describe the existing approaches taken to combat Spam 2.0, including the detection approach, the prevention approach, and the early detection approach. Three techniques based on the detection approach presented in this paper include: content based, metadata based and user flagging based. We also explore several open issues/problems in this area. These include problems regarding tools and technologies, awareness and responsibility, and spam and spammers. Issues discussed regarding awareness and responsibility are users' lack of awareness, governments' inaction in tackling Spam 2.0, companies' apathy in combating it, lack of collaboration between countries, and unclear accountabilities in this regard. The paper also identifies future trends for both anti-spammers and spammers. Anti-spammers will likely focus their efforts more on behaviour based techniques and produce more language independent tools. Implementation of dynamic forms and forcing every user to actually go through the registration form will be good ways to control spam. From a monetary perspective, estimating intangible costs associated with Spam 2.0 will help raise the awareness of public users regarding spamming. On the other hand, the spammers will predictably continue to find methods to decrease the filters' efficiency by imitating real users' behaviours and finding other spamming opportunities.