The increasing availability of Big Data, able to capture diverse collective phenomena, provides an unprecedented opportunity to explore the patterns underlying success. From the strategies followed by successful sportsmen to the emergence of runaway videos on YouTube, from popularity in social media to rising starts in the scientific enterprise, from widespread technologies to groundbreaking innovations, there is wealth of data that can be explored to answer common questions: How can we measure performance? What are the common patterns of success? How did successful individuals and products get to the top? What are the principles driving the dynamics of success? These are the challenging questions at the core of the emerging Science of Success, an interdisciplinary field that is attracting scientists from different scientific backgrounds.

The purpose of this workshop is to bring together researchers from a variety of areas, all working on the problem of analyzing and understanding the patterns of success, though from different angles. The aim is to discuss: 1) the recently developed machine learning and data mining techniques that can be leveraged to address challenges in analyzing performance and success, and 2) starting from challenges in analyzing performance and success, the practical research directions in the machine learning and data mining community.