Twitter earthquake detection: earthquake monitoring in a social world
Twitter earthquake detection: earthquake monitoring in a social world
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DOI：
10.4401/ag-5364
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发表时间：
2011-01-01
影响因子：
1
通讯作者：
Guy, Michelle
中科院分区：
文献类型：
--
作者：
Earle, Paul S.;Bowden, Daniel C.;Guy, Michelle
美国地质调查局（USGS）正在调查社交网站Twitter（一种用于发送和接收简短公共文本消息的流行服务）如何增强USGS地震响应产品和灾害信息的传递。对震动事件的快速检测和定性评估是可能的，因为人们在感觉到震动后开始发送公共Twitter消息（tweets）。在这里，我们提出并评估一个地震检测程序，完全依赖于Twitter的数据。由包含“地震”一词的推文构建的推文频率时间序列清楚地显示了与广泛感受到的事件的起源时间相关的大峰值。为了识别可能的地震，我们使用短期平均，长期平均算法。当调整到中等灵敏度时，探测器在五个月的数据中发现了48次全球分布的地震，只有两次错误触发。与美国地质勘探局全球地震目录中相同五个月时间段内的5，175次地震相比，检测到的数量很小，并且无法仅根据推文数据分配准确的位置或震级。然而，Twitter的地震探测并非毫无价值。这些发现通常是由广泛感受到的事件引起的，这些事件比没有人类影响的事件更直接。检测速度也很快;大约75%的检测发生在起始时间的两分钟内。这比在世界上仪器不足的地区进行地震探测要快得多。触发检测的推文还提供了经历过震动的人的非常简短的第一印象叙述。
The U.S. Geological Survey (USGS) is investigating how the social networking site Twitter, a popular service for sending and receiving short, public text messages, can augment USGS earthquake response products and the delivery of hazard information. Rapid detection and qualitative assessment of shaking events are possible because people begin sending public Twitter messages (tweets) with in tens of seconds after feeling shaking. Here we present and evaluate an earthquake detection procedure that relies solely on Twitter data. A tweet-frequency time series constructed from tweets containing the word "earthquake" clearly shows large peaks correlated with the origin times of widely felt events. To identify possible earthquakes, we use a short-term-average, long-term-average algorithm. When tuned to a moderate sensitivity, the detector finds 48 globally-distributed earthquakes with only two false triggers in five months of data. The number of detections is small compared to the 5,175 earthquakes in the USGS global earthquake catalog for the same five-month time period, and no accurate location or magnitude can be assigned based on tweet data alone. However, Twitter earthquake detections are not without merit. The detections are generally caused by widely felt events that are of more immediate interest than those with no human impact. The detections are also fast; about 75% occur within two minutes of the origin time. This is considerably faster than seismographic detections in poorly instrumented regions of the world. The tweets triggering the detections also provided very short first-impression narratives from people who experienced the shaking.