hacked some lua, got software logging what I needed; learnt python, parsed many text files; forked a cocoa app, classified laugh state for fifteen minutes times 16 audience members times two performances; and so on. eventually, a dataset of meascollect audience response for every tenth of a second. and with that: results. statistics. exciting.

a teaser of that is above, peer review needs to go it’s course before announcements can be made. as a little fun, though, here is the introduction of the paper the first results are published in – at some point before it got re-written to fit house style. this has… more flavour.

Live performance is important. We can talk of it “lifting audiences slightly above the present, into a hopeful feeling of what the world might be like if every moment of our lives were as emotionally voluminous, generous, aesthetically striking, and intersubjectively intense” \cite{Dolan:2006hv}. We can also talk about bums on seats and economic impact — 14,000,000 and £500,000,000 for London theatres alone in recent years \cite{Anonymous:2013us}. Perhaps more importantly, it functions as a laboratory of human experience and exploration of interaction \cite{FischerLichte:2008wo}. As designers of media technologies and interactive systems this is our interest, noting the impact of live performance on technology \cite{Schnadelbach:2008ii, Benford:2013ia, Reeves:2005uw, Sheridan:2007wc, Hook:2013vp} and how technology transforms the cultural status of live performance \cite{Auslander:2008te, Barker:2012iq}. However, as technology transforms the practice of live performance, the experiential impact of this on audiences is surprisingly under-researched. Here, we set out to compare this at its most fundamental: audience responses to live and recorded performance.