Finding Influences in a Network

Our work involves developing statistical methods to identify “who influences whom” in networks. Examples include neuroscience (which cells connect to which cells?), social networks (whose tweets are ‘viral?’), and financial networks (does the French GDP affect U.S. housing prices?).

We will review recent theoretical work on optimally approximating networks (of my 700 Facebook friends, which four matter the most?) and recent data analysis.