Twitter Earthquake Detection (TED) System by USGS
U.S. Geological Survey (USGS) Seismologists say Twitter is the fastest way to get information out of an earthquake area, especially in those less densely populated with seismic instruments.
After an earthquake, people often rapidly report that an earthquake has occurred and describe what they have experienced, and tweet it. Those quick, early reports are able to come out of the epicenter faster than the existing detection and reporting systems. For felt earthquakes in populated regions, Twitter reports often precede the USGS’s publicly-released, scientifically-verified earthquake alerts.
The USGS is investigating the use of Twitter, a popular micro-blogging tool, to collect and analyze citizen accounts of earthquakes around the world. The USGS has initiated Twitter Earthquake Detection (TED). Twitter account for the TED project is @USGSted.
TED uses the Twitter social networking platform to collect real-time, earthquake-related messages from anywhere around the globe. For earthquakes in sparsely instrumented regions, these detections could provide an initial heads up that an earthquake may have occurred.
TED uses an application programming interface that aggregates tweets based on keywords like “earthquake” and “tremor” to pull tweets about a particular earthquake into a database. Then the USGS generates an e-mail report containing the magnitude, location, depth below the surface, number of tweets about the earthquake broken down by their location, and text of the first 40 or 50 tweets. The system may help the USGS locate earthquakes that are too small to be detected by its network of sensors.
TED will not replace any existing systems of USGS, instead it is used in conjunction with or alongside existing systems.
One drawback of TED is that, not all Twitter users provide locations. Or they may provide only a city such as Los Angeles as their location. So this information is very vague compared to a tweet that comes from a GPS-enabled mobile device which would provide a latitude-longitude Twitter accurate within city blocks.
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