Abstract

Following the 12 May 2008 Wenchuan, China, earthquake, discussion circulated on the Internet describing how the U.S. Geological Survey's earthquake notification lagged behind firsthand accounts sent through Twitter, a popular Internet-based service for sending and receiving short text messages, referred to as “tweets.” A prominent technology blogger, Robert Scoble (http://scobleizer.com), is generally credited for being the first to aggregate and redistribute tweets from people in China who directly experienced and reported the shaking resulting from the Wenchuan earthquake. Subsequent earthquakes generated volumes of earthquake-related tweets, and numerous accounts are on the Web. For example, Ian O'Neill discusses Twitter activity following a magnitude 3.3 Los Angeles earthquake on 24 January 2009 in his blog http://astroengine.com. He showed a remarkable increase in frequency of tweets containing the word “earthquake” after the event and discussed the possibility of a Twitter-based earthquake detector. Similarly, following the 30 March 2009, Morgan Hill, California, magnitude 4.3 earthquake, Michal Migursk (http://mike.teczno.com) noted an increase in earthquake-related tweets. Access to firsthand accounts of earthquake shaking within seconds of an earthquake is intriguing, but is there any reliable information that can be gleaned from the Twitter messages? To explore this question, we provide a quick review of Twitter and its capabilities and investigate the possibility of using the tweets to detect seismic events and produce rapid maps of the felt area. In this exploratory study, we examine the tweets that followed the 30 March 2009 Morgan Hill earthquake. Twitter is a service that allows anyone to send and receive 140-character text messages (tweets) via any Internet-enabled device. Tweets can be sent and received through a Web page, mobile device, or third-party Twitter applications. Tweets can be sent publicly or privately to a specified user. All users who opt to “follow” a Twitter user will receive that user's tweets …

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