Article: Automatically Identifying Eyewitness Reporters on Twitter During Disasters

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Automatically Identifying Eyewitness Reporters on Twitter During Disasters

My colleague Kate Starbird recently shared a very neat study entitled “Learning from the Crowd: Collaborative Filtering Techniques for Identifying On-the-Ground Twitterers during Mass Disruptions” (PDF). As she and her co-authors rightly argue, “most Twitter activity during mass disruption events is generated by the remote crowd.” So can we use advanced computing to rapidly identify Twitter users who are reporting from ground zero? The answer is yes.

An important indicator of whether or not a Twitter user is reporting from the scene of a crisis is the number of times they are retweeted. During the Egyptian revolution in early 2011, “nearly 30% of highly retweeted Twitter users were physically present at those protest events.” Kate et al. drew on this insight to study tweets posted during the Occupy Wall Street (OWS) protests in September 2011.

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