Causal Impact

Today's episode is all about Causal Impact, a technique for estimating the impact of a particular event on a time series. We talk to [William Martin](http://www0.cs.ucl.ac.uk/staff/W.Martin/) about his research into the impact releases have on app and we also chat with [Karen Blakemore](https://twitter.com/kjblakemore) about a project she helped us build to explore the impact of a Saturday Night Live appearance on a musician's career.

Martin's work culminated in a paper [Causal Impact for App Store Analysis](http://www0.cs.ucl.ac.uk/staff/W.Martin/pubs/Martin_FSE_Causal_PrePrint.pdf). A shorter summary version can be found [here](http://www0.cs.ucl.ac.uk/staff/W.Martin/pubs/Martin_ACM_SRC_cameraReady.pdf). His company helping app developers do this sort of analysis can be found at [crestweb.cs.ucl.ac.uk/appredict/](http://crestweb.cs.ucl.ac.uk/appredict/).

Guests

William Martin: I completed my undergraduate degree at UCL in 2012 in Computer Science. I worked with others on the Newton Spectrum corpus browser, and then extended the system to incorporate a topic modelling based cluster visualisation. In my final year I worked on an automated method for correcting topic model coherence through external bias. I am currently a PhD candidate in Computer Science at UCL Crest centre, in the area of App Store Analysis.

Karen Blakemore