A multi-language approach towards the identification of suspicious users on social networks

The use of IT technology for the planning and implementation of illegal activities has been gaining ground in recent years. Nowadays, through the web and the social media, it is possible not only to divulge advertising for the disclosure of illicit activities, but also to take action that in the past needed to have people in place and at the moment the activity took place. In fact, this phenomenon allows criminals to be less exposed to the risk of being discovered. Furthermore, the technology tends to encourage international collaborations, which makes the process of identifying illegal activities even more complex because of the lack of adequate tools that can operate effectively by considering multi-cultural aspects. Consequently, this evolving phenomenon towards cyber-crime requires new models and analysis techniques to address these challenges. In this context, the paper proposes an approach based on a multi-language model that aims to support the identification of suspicious users on social networks. It exploits the effectiveness of web translation services along with specific stand-alone libraries for normalizing user profiles in a common language. In addition, different text analysis techniques are combined for supporting the user profiles evaluation. The proposed approach is exemplified through a case study by analyzing Twitter users profile by showing step by step the overall process and related results.