This document summarizes a research paper on collaborative personalized tweet recommendation. The paper proposes a model that incorporates latent topic factors to capture users' interests, social latent factors to model relationships, and explicit features. It builds on traditional collaborative ranking approaches. The model is evaluated on a dataset of over 80,000 tweets and shown to outperform baselines in recommending tweets a user may want to retweet.