1. A computer-implemented method, comprising: obtaining, with one or more processors, a first stream of candidate content items based on a request from a user; generating, with the one or more processors, a model stored in a memory coupled to the one or more processors based on an interest of the user and a prior interaction of the user; computing, with the one or more processors, an interestingness score for each of the candidate content items based upon a comparison of each of the candidate content items to the model stored in the memory, a quality of each candidate content item, and information relating to relationships of users from a social graph of the user, wherein the interestingness score represents similarities between attributes of the candidate content item and the model stored in the memory and the quality of each candidate content item is based on at least one of a popularity, an importance and a relevance of the respective candidate content item; determining a threshold for the first stream of candidate content items based on an extent to which the popularity of the candidate content items has changed in a user's location; comparing, with the one or more processors, the interestingness score of each of the candidate content items with the threshold to determine which candidate content items have an interestingness score that exceeds the threshold; organizing a first content item and a second content item that have the interestingness score that exceeds the threshold in a second stream of content; and providing the second stream of content along with an explanation for why the first content item and the second content item are included in the second stream of content for display on a user interface of a client device associated with the user that submitted the request, wherein the user interface includes at least one button associated with each of the first content item and the second content item, which, once selected by the user, causes the one or more processors to receive a feedback to the explanation and to automatically update the model and the second stream of content based on the feedback.