Predicting popularity and success in cultural markets is hard due to strong inequalities and inherent unpredictability. A good example comes from the world of fashion, where industry professionals face every season the difficult challenge of guessing who will be the next seasons’ top models. A recent study by CNetS graduate student Jaehyuk Park, research scientist Giovanni Luca Ciampaglia (also at the IU Network Science Institute), and research scientist Emilio Ferrara (now at the University of Southern California) is now showing that early success in modeling can be predicted from the digital traces left by the buzz on social media such as Instagram. The study has been accepted for presentation at the 19th ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW’16). The work has been covered in the media by the MIT Technology Review, Die Welt, Fusion, and iTNews.