SocRec is a social-oriented recommender system developed for iPad that allows the aggregation, filtering, tagging and rating of content pulled from three popular social media (Flickr, YouTube, and LastFM).

SocRec screenshot

Social features have been included by means of Facebook API and OAuth identification. The user can login using his/her FB identity (passwords are not saved into our application) and then can search wanted media accross different Web services. The user is allowed to tag and rate content to let a remote server learn something about his/her interests and tastes. If the given application is spread accross friends of the user, the remote recommender service starts to personalize suggested content on the basis of most popular content in a person's friendship network, and on the basis of common interests with other users. Communication with our remote recommender service is implemented through calls to our X-Hinter's API (more information here).

Projects. An early version of SocRec has been implemented within SIPLab (Social Information Processing Laboratory), that has been supported by our department and CSP, from 2009 to 2011. After that, a modified version of this software have been used for a comparative usability analisys within project IS4.Mobi.