For the last 374 days, I have been sharing my feelings with my iPhone.
Happy, relaxed, awake or watching TV, reading or in the gym, I’ve been recording what mood I’m in.
This strange behaviour is thanks to a LSE project called Mappiness – the happiness mapping app. It’s a tool built by a group of researchers interested in finding out what affects a person’s environment has on their well-being.
The app is also part of a wider movement of people interested in self-measurement; Quantified Selfers using technology to create large sets of data about oneself, from pulse rate to calorie intake.
Mappiness pings me twice a day and asks me how ‘happy’, ‘relaxed’ or ‘awake’ I am on a sliding scale, then asks a few questions about who I’m with and what I’m doing.
I’ve now got a year’s worth of data – enough to be statistically significant – and I also promised the Mappiness team I’d write up a bit of user feedback.
So here are a few things Mappiness has taught me over the last year:
- I get gradually more grumpy towards the middle of the week – Wednesdays are my low point and the weekends are my peak.
- I’m not a morning person – I get significantly happier later in the day.
- I am happiest when traveling on the bus. I can’t explain that one.
- I don’t like being on my own.
- The thing I do most is working – or at least that’s when I’m most likely to respond to the app. Followed by listening to music (which I know I do mostly when working), followed by socialising, followed by commuting and eating – a fairly accurate and somewhat depressingly routine picture.
And here are a few thoughts for the Mappiness team:
1.) Awake vs tired
The first question the app asks is how happy, relaxed and awake you are. I don’t know how the original questions were decided on, but asking how ‘tired’ you are, rather than how ‘awake’ you are might be more useful. I can be wide awake but utterly exhausted – and there are few things that cause me to be more irritable than tiredness.
2.) User experience
The next few questions ask who you’re with and what you’re doing, and there are quite a lot of choices. Judging by my answers, I spend the majority of my time doing about five of the 40 or so options. If my most frequent choices were automatically nearer the top of the page that would probably make it a little quicker to submit my answers.
3.) Richer learning from combining data differently
Mappiness provides you with a set of charts displaying the data you’ve collected in an easy-to-interpret format. The last of these I’ve found the least interesting – ‘What am I happiest doing?’ – because it doesn’t record a combination of activities.
So you can’t tell if listening to music and eating is making you happier than just listening to music, and so forth. I think there a few ways to provide a richer combination of data here, without me extracting it and working out for myself. I don’t think the default option tells you very much.
This is just brilliant – http://www.mappiness.org.uk/meters/ – the UK’s happiness in real time. There are so many things you could try mapping this data against to see what patterns you find: weather, sunset/sunrise, news stories, economic growth…. I can’t remember what personal information the app collects when you sign up, but I’d be interested to see the demographic spread of Mappiness users.
Lots of friends have commented that they downloaded the Mappiness app but stopped using it after their curiosity waned. They’re typically pretty surprised that I’m still updating it because they can’t understand what I get back from it.
I suppose I’ve kept using it because I think well being is an interesting concept in itself and it’s become a bit of a conversation point. But if you’re really looking for a large number of people to use it, you need to offer them something more useful back than just raw data.
This is a challenge for many of the Quantified Self products. Ultimately, assuming these ideas become more mainstream, it will partly be about saving money; insurance companies offering premium discounts for your data or supermarkets offering tailored deals. This is just another form of store loyalty card that already exist.
For me, I want to make the data personally useful. Mappiness is starting to get a picture of when I’m likely to be most grumpy (Wednesday morning is a prime moment) and it could easily ping me and make a suggestion to cheer me up based on what I’m doing when I seem to be happiest. For example, it could remind me to take my gym kit when I left the house on Wednesdays, since I report to be pretty content when I’m exercising.
Now I’m in the US, my data is no longer part of the research project, but I’ll be keeping an eye on this every once in a while, just to check what’s going on in the homeland.