Mining Deep Twitter To Turn History into a Storify
This week marks the fifth anniversary of the horrific terrorist attacks in Mumbai, India. Over the course of three days, chaos ruled across the city formerly known as Bombay, as terrorists targeted hotels, cafes and train stations. It was one of the first major international news stories to break out across Twitter, before the Arab Spring and the 2009 Iranian election protests – and for me, it became one of the most difficult stories to reconstruct so many years after the fact.
I’ve been using Storify to create social media narratives since late 2010, and put it to use frequently during the protests and revolutions around the Arab World. While it was sometimes time-consuming, it was relatively straightforward, as I could construct each Storify in real time, or soon after a particular event took place. Social media has always been extremely ephemeral, so the faster I could build out a Storify, the greater likelihood I’d be able to capture whatever social media I was interested in documenting.
Back in November 2008, though, things were very different. There weren’t any social media archiving tools like Storify. Tweets contained relatively limited amounts of metadata. And it didn’t occur to most of us to make note of all of this historic tweets to utilize them later.
Fast forward to November 2013. All of those tweets from five years ago still exist. They’re part of Deep Twitter, buried in the archives and very difficult to surface through typical search results. Nonetheless, I wanted to reconstruct what happened that fateful week using Storify. This is how I went about doing it – and it wasn’t particularly easy.