FRAppE: Detecting Malicious Facebook Applications

Online social media services like Facebook witness an exponential increase in user activity when an event takes place in the real world. This activity is a combination of good quality content like information, personal views, opinions, comments, as well as poor quality content like rumours, spam, and other malicious content. Even if the good quality content makes online social media very good source of information, uses of bad quality content can degrade user experience, and could have an inappropriate impact in the real world. It could also impact the enormous promptness, promptness, and reach of online social media services across the globe makes it very important to monitor these activities, and minimize the production and spread of bad quality content. Multiple studies in the past have analysed the content spread on social networks during real world events. However, little work has explored the Facebook social network. Two of the main reasons for the lack of studies on Facebook are the strict privacy settings, and limited amount of data available from Facebook, as compared to Twitter. With over 1 billion monthly active users, Facebook is about times bigger than its next biggest counterpart Twitter, and is currently, the largest online social network in the world. In this literature survey, we review the existing research work done on Facebook, and study the techniques used to identify and analyse poor quality content on Facebook, and other social networks. We also attempt to understand the limitations posed by Facebook in terms of availability of data for collection, and analysis, and try to understand if existing techniques can be used to identify and study poor quality content on Facebook