Mappiness: Mapping Happiness

A shot of the app.

From the blog How Do you Landscape; a group from the UK has created an app that can be used to measure our happiness based on our surroundings, and using maps to look at the data:

“People feel better outside than inside”. “People feel better in the park/woods/nature than in the city”. These are some of the conclusions from a project with the telling title ‘Mappiness’ Good news for landscape and Landscape Architecture on first sight. But are these only one-liners or firmly based scientific statements? Well, that depends on the quality of the empirical evidence of course. Most experience sample methods (ESM) have a hard time getting a representative group (in the end almost only colleagues) that has to struggle trough tedious interview forms (“it will take only twenty minutes”) to step-by-step end up with modest results. How about a sample group of 47.331 people (and growing by the day) who willingly support their data three times a day to the researchers that by now collected over three million forms in a few months? I stumbled upon these remarkable Experience research feats in a TedxBrighton 2011. In this “Twenty minutes lectureGeorge MacKerron explains why and how he and Susana Mourato (both from the Department of Geography & Environment at the London School of Economics and Political Science) created ‘mappiness’. They want to better understand how people’s feelings are affected by features of their current environment. Things like air pollution, noise, and green spaces influence your well being is their hypothesis.

This is how it works. They developed an app that can be downloaded for free. It must be one of the most irritating apps around on the web because it rings you (with your approval, you can influence the settings) three times a day to ask you three simple questions.

When put through a big regression model they can gauge the happiness as the function of habitat type, activity, companionship, weather conditions (there is of course a link between meteorological data and the GPS data), daylight conditions, location type (in, out, home, work, etc), ambient noise level, time of the day, response speed, and individual ‘fixed-effects’ (that come out of your personal Mappiness-history). Factors can be plotted out against each other.

How awesome is that? What a neat piece of technology to measure our surroundings and how they influence us!

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