The great Nairobi guesthouse swimming pool dilemma – cast your vote now……

January 26, 2012

Wrapping up the great Nairobi guesthouse pool debate

January 26, 2012

The realtime challenge: some cutting edge data-gathering from the UN (yep, you heard that right)

January 26, 2012
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I’m still reeling from the overwhelming response to yesterday’s post (voting still open, by the way) and will respond in due course, but in the meantime, let’s get back to all that development stuff, shall we? One of the most striking aspects of exploring the human impact of the global financial crisis and food price spike was the absence of realtime data: a shock happens, and we hear about certain variables – GDP, prices, even unemployment in some countries – in real time. But other aspects – especially the impact on the way people live their lives – take months or often years to emerge. We had a go at doing some realtime monitoring of, for example, the gender impact of the financial crisis, and (with IDS) the community impact of the price spike. What we haven’t done yet is harness the spread of mobiles and the internet in that task.

Step forward the UN. Here’s a fascinating ten minute presentation of five ground-breaking data crunching experiments from the UN’s GlobalGlobal Pulse logo Pulse project, trying new ways to  follow realtime events. The first uses mobile phones to survey wellbeing around the world as a first step to inform the design of more exhaustive surveys. Next up is using prices of online food (e.g. on developing country supermarket websites) as a low-cost, realtime way to follow food prices. Third is tracking shifts in global opinion by tracking news coverage via key words and phrases and watching how they evolve over time. Fourth shows how monitoring online conversations (eg blogs, twitter) can help follow unemployment trends – in the US the language of anger (and cancelling vacations)  precedes job losses, whereas in Ireland it is talk of anxiety. Finally, the enthusiastic tweeters of Indonesia talk about food a lot, and the frequency pretty much matches food prices. Much more to come, with a focus on Indonesia and Uganda.

Please send links to your own favourite examples of this kind of exercise. [h/t Richard King]


  1. Fascinating post Duncan. What’s your view on the issue of selection bias here i.e. capturing views of those with a mobile phone rather than those who are suffering highest levels of food insecurity?

    1. Fair point, Ross, and I think the video makes it clear that this is a genuine issue, and means we should see these methods as additional to more rigorous approaches, eg helping in questionnaire design etc

  2. ….the pity is that from many countries in Africa (I am based in Nouakchott, Mauritania), it is just impossible to have a fair enough internet connection to watch teh video…so more than a sampling bias, it is a technological GAP. I know or heard that modern information technology is making a breaktrough in Africa, but we are highly lagging behind. Linked to the subject, any suitable timely data collection should take this in consideration, including our own capacity to just understand the issues at stake if we are not timely connected

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