Crowdsourced election protection

August 20, 2009 at 11:32 am 1 comment

In following innovative uses of SMS (text) messaging, I’ve been delving into the work of Ushahidi. The name means “testimony” in Swahili, and the platform crowdsources crisis information such as political upheavals or natural disasters. Anyone can submit updates through text messaging using a mobile phone, email or web form.

Ushahidi was developed to map reports of violence in Kenya after the post-election fallout at the beginning of 2008.

In breaking news, Alive in Afghanistan is using the Ushahidi mapping system to report election irregularities.

Map of citizen-reported Afghan election irregularities

Text messages are collected via Frontline SMS, another great system which uses free open source software to turn a laptop + mobile phone into a central communications hub. Easy to set up, portable, and resilient: just what is needed in chaotic circumstances.

The next issue is what to do with the flood of information that comes in beyond a heat map of incidence reporting. What do you pull out of the SMS or Twitter stream? What’s credible? What’s important? In particular, how do you deal with the first three hours of a crisis? Ushahidi founder and TED fellow Erik Hersman is tackling that problem now.

Graph: Quantity vs. quality of hour by hour crisis reporting data

A small team at Swift River is looking to the crowd to filter data as well as generate it.

Swift … is an initiative that seeks to do two very important things, both of which are crucial for not just Ushahidi, but for many emergency response activities in the future. First, it gathers as many possible streams of data about a particular crisis event as possible. Second, using a two-part filter, that stream of data is filtered through both machine based algorithms and humans to better understand the veracity and level of importance of any piece of information. –Erik

See it in action at Vote Report India.

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Entry filed under: Current Events, Engineering, ICT4D, Social Media. Tags: , , , , , , , , , .

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