UPDATE: Video of this presentation is now available online.
Next week we have Alex Schulz from the Technical University of Darmstadt who will giving a talk about his work on using social media data along with machine learning, and semantic dictionaries (i.e., WordNet), to automatically detect small scale incidents, such as car crashes, shootings, and fires.
I saw Alex present a paper co-authored with Petar Ristoski at ICWSM during a really interesting workshop titled When the City Meets the Citizen. In that paper they analyzed Twitter data from Seattle and Memphis. One of their findings was that average citizens (labeled I and blue in the figure below) were often the first to report shootings (53% of the time), much earlier than other people that one would expect such as Emergency Management Organzations (EMO), journalists/bloggers devoted to emergencies (EMJ), general journalists/bloggers, or other types of governmental and non-governmental organizations (ORG).