Discriminating Between the Wheat and the Chaff in Online Recommendation Systems

MyChoice is an ambitious research project that aims to model, detect, and isolate outliers (aka fake) in online recommendation systems, as well as in online social networks. The final outcome of the project will be the prototype of an automated engine able to recognize fake information, such as reviews, and fake friends/followers, and able to filter out malicious material, in order to return reliable and genuine content to the user . MyChoice aims to provide novel models and tools to search genuine and unbiased content on Web platforms, while filtering out partial and fake information. The expected outcome of the project is twofold: firstly, focusing on real online recommendation systems, MyChoice intends to tackle the (malicious) bias that may influence a high percentage of users. Secondly, the project pays attention to fake accounts on social networks and provides automatic fake detection techniques. As an example on Twitter, "fake followers" are those accounts created to inflate the number of followers of a target account, to make it more trustworthy and influential, in order to stand out from the crowd and attract other genuine followers.