Seismologists say Twitter could be the fastest way to get information out of an earthquake area, especially in those less densely populated with seismic instruments.
People love to tweet about what's going on around them, especially when that something is exciting or otherwise newsworthy. And what could be more exciting or otherwise newsworthy than an earthquake? As it turns out, not much. "People like to tweet after earthquakes," says USGS Seismologist Paul Earle, in a recent episode of the USGS CoreCast. "After an earthquake," Earle adds, "they often rapidly report that an earthquake has occurred and describe what they’ve experienced." And 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," said Earle.
The energy behind that kind of behavior is what is behind the Twitter Earthquake Detection (USGSted) project Dr. Earle is heading up. 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," explains Earle.
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. "As you get outside the United States and in some regions of the United States, the seismographic network is very sparse," Earle said. "So you'll get these tweets in before you can actually locate it with our system."
Twitter is fast, but not without a few hiccups
Tweeting about earthquakes is hardly new -- at least in twitter years. People turned to twitter during an earthquake in Southern California in July, 2008, after they finding they were unable to make or receive any cell phone calls, they could still use twitter via SMS or another mobile twitter app. And Twitter's potential as an an emergency communication tool is being considered for other applications as well.
"If somebody is saying, 'My house is on fire' and it's an area that has wildfires, well, obviously that's not official data," said Federal Emergency Management Agency director Craig Fugate in a recent interview with TechPresident. "But they're telling us their house is burning down. They're shooting video of their house on fire. I consider that pretty good information."
Twitter certainly has its limits as an earthquake reporting and detecting tool, and will not be replacing USGS' Did You Feel It? or ShakeMaps any time soon. But scientists see value in the social platform if it is used in conjunction with or alongside existing systems. Where USGSted soars (speed, ease of use, low barriers to entry, an existing and essentially free platform), it also meets its limits: A twitter-based system limits message length to 140 characters; the social component of twitter also creates a host of filtering and clustering challenges (retweets and casual uses of earthquake-related words like references to the video game 'Quake' need to filtered out); and finally, not everyone has geo-tagging enabled, which can provide inconsistent, and otherwise low-utility tweets.
Also, most 'quake-centric' tweets will generally lack a ton of hard data, instead falling into the 'qualitative data' camp. These are usually personal reactions, quick recollections and little bits of narrative that can help capture descriptive dimensions of earthquakes that hard scientific data might not adequately capture.
Earle and his team at USGS know that they have just scratched the surface of combining qualitative, narrative data with quantitative scientific measurements. But as new Web 3.0 systems emerge, there will be ever more ways to tag tweets with the kind of metadata--seismic and otherwise--that will further blur the distinction between the soft and hard sciences.