Predicting the next Arab Spring through Twitter data

Predicting the next Arab Spring through Twitter data

Big data: "A visual rendering of tweets and retweets from a several-hour period on February 11, 2011, starting shortly before the resignation of Egyptian President Hosni Mubarak."

In "Pictures at a Revolution" in Foreign Policy, Luke Allnutt makes a striking case for using "big data" to predict the timing, location and nature of the next major social upheaval, and harnessing similar data to improve how we help the world's most vulnerable populations.

As more people get online around the world, especially through their cheap smart phones (of which there are now some 4 billion), data streams will proliferate and most segments of society will reveal themselves through various kinds of social media data.

We're already seeing cases in which visualized data enable policy makers to make quick informed choices about public health, poverty, or energy efficiency. Google Flu Trends, which estimates current flu activity around the world in real-time by monitoring search terms, has been shown to predict confirmed cases of flu with a level of accuracy comparable to the Centers for Disease Control and Prevention.

By looking at different tag clouds over time, we can perhaps even see terms reflect a general shift from awareness/advocacy towards organization/mobilization, and eventually action/reaction.

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