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Analyzing Malicious users on Social Networks Using Smart Sense Methods

Luis Miguel Vaquero, Sergey Volkov


In recent years, Online Social Networks (OSNs) have dramatically expanded in popularity around the world. According to the data in October 2012, Facebook has 1.01 billion people using the site each month.1 Moreover, the numbers of users in five popular OSNs are listed in Table 1. The rapid growth of OSNs has attracted a large number of researchers to explore and study this popular, ubiquitous, and large-scale service. In this article, we focus on understanding user behavior in OSNs. The tools for social media network analysis and visualization have been emerging from many research groups and startup companies. These pioneering network analysis tools often require programming skills and knowledge of technical network terminology, making it a challenge for those without programming skills to import and make sense of network data. In this paper a detailed study on identification of malicious users has been carried.


Spammers Detection, Behaviour based Social Media Analysis,

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