Introduction

Abstract

Human interactions facilitated by social media, collaborative platforms, and the blogosphere generate an unprecedented volume of electronic trace data every day. These traces of human behavior online are a unique source for understanding contemporary life behaviors, beliefs, interactions, and knowledge flows. The social connections we make online, which reveal multiple types of human connection, are also recorded on a scale and to a level of granularity previously unimaginable, except possibly by science fiction writers. To many in the data analytics world, these traces are a gold mine. New sub-domains of inquiry have emerged as a consequence of this revolution: computational social science, big data, data science, open innovation data analytics, network science, and undoubtedly new ones yet to appear in the near future. Massive amounts of data, each counting millions of data records and behaviors, are now available to the academic, governmental, or industry research and teaching communities. They promise faster access to real-time social behavior and better understanding of how people behave and interact. Such “social” data include complete records of Wikipedia edits, interactions on social coding platforms like GitHub, and the expression of affiliations and engagement of participation on social media (Twitter, Facebook, YouTube, etc.).