GIFGIF is a project created by Kevin Hu and Travis Rich at MIT Media Lab that aims to build up a library of non-verbal communication. Presented as a light-hearted game the user is presented with two Gifs, randomly generated from the extensive giphy library and must choose which better expresses a particular emotion such a guilt, embarrassment, pleasure. Does Mischa Barton breaking out a huge grin or One Direction cringing-ly cocking their heads better express 'surprise'? You decide.

As more responses are recorded the Media Lab team will be able to build up a repository of quantitative data about our perception of facial expressions and physical responses to emotions. In a similar vein to many online citizen science projects GIFGIF is relying on the sheer quantity of people it can reach through the internet to analyse images and emotions, something that computers are not particularly good at. This will result in a library of GIFs that is searchable by the emotion they cause rather than manually entered tags. GIFGIF will also provide insight into how people from different countries react to GIFs, Hu and Rich are interested to see if the emotional response to a GIF differs across cultures – is the perception of happiness to a Brit very different than for an American?

GIFs have become an important part of digital culture - so much so they even have their own awards the .GIFYS – and once categorised by emotion they will communicate the currently incommunicable via a simple search.