Disentangling the Lexicons of Disaster Response in Twitter
Disentangling the Lexicons of Disaster Response in Twitter
复制标题
理清 Twitter 中的灾难响应词汇
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Courtney Corley
中科院分区：
文献类型：
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作者：
Nathan Oken Hodas;G. V. Steeg;Joshua J. Harrison;Satish Chikkagoudar;Eric Bell;Courtney Corley
世界各地的人们使用Twitter等社交媒体平台来表达他们的意见并分享有关日常生活各个方面的活动。就像社交媒体改变日常生活中的沟通方式一样，它也在改变人们在灾难和紧急情况下的沟通方式。由于应急官员已经开始依赖社交媒体来传达警报和更新，他们必须了解用户如何在社交媒体上传达与灾难相关的内容。我们使用了一种新的信息理论无监督学习工具CorEx来提取和描述公众在已知紧急情况下（如火灾、爆炸和飓风）在Twitter上使用的高度相关的内容。使用由此产生的分析，当局可能能够对社交媒体内容进行评分，并优先关注那些最有可能与灾难有关的消息。
People around the world use social media platforms such as Twitter to express their opinion and share activities about various aspects of daily life. In the same way social media changes communication in daily life, it also is transforming the way individuals communicate during disasters and emergencies. Because emergency officials have come to rely on social media to communicate alerts and updates, they must learn how users communicate disaster related content on social media. We used a novel information-theoretic unsupervised learning tool, CorEx, to extract and characterize highly relevant content used by the public on Twitter during known emergencies, such as fires, explosions, and hurricanes. Using the resulting analysis, authorities may be able to score social media content and prioritize their attention toward those messages most likely to be related to the disaster.