Keynote speakers: Big data science and social networks — Accelerating insights and building value

Knowledge discovery has been driven by theory, experiments and by large-scale simulations on high-performance computers. Modern experiments and simulations involving satellites, high-throughput instruments, sensors, and supercomputers yield massive amounts of data. What has changed recently is that the world is creating massive amounts of data at an astonishing pace and diversity. Concurrently, social communities such as Facebook, Twitter, Google, and others are creating massive amounts of data at an astonishing pace. But, even more complex is the network that connects the creators of data. There is knowledge to be discovered in both for actionable insights. In this talk I present that processing, mining and analyzing this data effectively is a critical component for knowledge discovery. And we can no longer rely upon traditional ways of dealing with the data due to its scale and speed. In particular, I present approaches and many examples to derive science and business value. Examples include deriving knowledge from massive data for marketing and other applications, understanding sentiments, determining influencers based on dynamic networks. Particular examples from major social networks will be used. Then I connect the applicability of approaches to addressing important science problems including in climate change understanding and medicine.