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How Twitter confirmed the explosion in Harlem first | DesignNotes by Michael Surtees
Harlem_Explosion_03

How Twitter confirmed the explosion in Harlem first

There’s a post on Gigaom from Ted Bailey of Dataminr talking about how were were able to verify the sad explosion in Harlem before local news. Titled How Twitter confirmed the explosion in Harlem first, he breaks done some of the factors involved verifying.

In just the first minutes after the Harlem explosion, aggregate Twitter data revealed a lot about what had happened. People acted collectively as an on-the-ground detection and sensory network, depicting the scene with granularity long before first responders or reporters arrived.

These Twitter eyewitnesses in Harlem provided a mosaic of images and first-hand accounts — all emerging from one location in a short time. Additionally, the geo-proximity of tweets, the shape and rate of tweet propagation, and the linguistic signatures of the messages quickly illustrated the potential magnitude and importance of what had occurred — all before traditional information sources had even arrived on site.

According to the NYC Fire Department, the explosion took place around 9:31 AM EDT. Twelve minutes passed before local news reported that a serious event had occurred. It wasn’t until 20 minutes after the explosion that the first major news coverage of the tragedy appeared. A wealth of detailed information flowed through Twitter immediately following the explosion and continued throughout those first 12 minutes — and well beyond.

The graphic below shows a set of geo-localized tweets that Dataminr algorithms clustered together during these initial 12 minutes. Before any single source could confirm the event, the truth was already in the tweets. The unique pattern of tweets painted a specific picture confirming the event was in fact happening and that the people tweeting thought it was a “big deal.” The descriptions in the tweets provided raw and important insight into how these eyewitnesses were experiencing the event in real-time.

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