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首页> 外文期刊>International journal of information systems for crisis response and management >Multilingual Analysis of Twitter News in Support of Mass Emergency Events
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Multilingual Analysis of Twitter News in Support of Mass Emergency Events

机译：支持大规模突发事件的Twitter新闻的多语言分析

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摘要

Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this article the authors study the problems of analyzing multilingual twitter feeds for emergency events. Specifically, they consider tsunami and earthquakes as one possible originating cause of tsunami. Twitter messages provide testified information and help to obtain a better picture of the actual situation. Generally, local civil protection authorities and the population are likely to respond in their native language. Therefore, the present work focuses on English as "linguafranca " and on under-resourced Mediterranean languages in endangeredzones, particularly Turkey, Greece, and Romania. The authors investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks.
机译：从某种意义上说，社交媒体可以帮助发现自然灾害并在灾害期间或灾害后支持危机管理，因此越来越成为基于事件的预警系统的来源。在本文中，作者研究了针对紧急事件分析多语言Twitter提要的问题。具体来说，他们将海啸和地震视为海啸的一种可能起因。 Twitter消息提供了经过验证的信息，并有助于更好地了解实际情况。通常，地方民防部门和民众可能会以其母语回答。因此，目前的工作着眼于英语作为“ linguafranca”，以及濒临灭绝地区特别是土耳其，希腊和罗马尼亚的资源匮乏的地中海语言。作者调查了十个地震事件，并定义了四个特定于语言的分类器，这些分类器可通过过滤掉与该事件无关的消息来检测地震。最终目标是将这项工作扩展到更多的地中海语言，并从推文中分类和提取相关信息，并将主要关键字翻译成英语。初步结果表明，这种过滤器有可能确认海啸预报参数影响沿海地区，那里没有潮汐仪，可以将其整合到地震传感器网络中。

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