Recent studies on people recommendation have focused on suggesting people the user already knows. In this work, we use social media behavioral data to recommend people the user is not likely to know, but nonetheless may be interested in. Our evaluation is based on an extensive user study with 516 participants within a large enterprise and includes both quantitative and qualitative results. We found that many employees valued the recommendations, even if only one or two of nine recommendations were interesting strangers. Based on these results, we discuss potential deployment routes and design implications for a stranger recommendation feature. Copyright 2011 ACM.