Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach
Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach
复制标题
将社交媒体整合到泛欧洲洪水意识系统中：多语言方法
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
P. Salamon
中科院分区：
文献类型：
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作者：
Valerio Lorini;Carlos Castillo;F. Dottori;M. Kalas;D. Nappo;P. Salamon
本文介绍了一个原型系统，将社会媒体分析集成到欧洲洪水预警系统（EFAS）。这种集成允许由水文气象模型确定的洪水风险警报自动触发社交媒体数据的收集。然后，我们采用多语言的方法来找到洪水相关的消息，采用两个国家的最先进的方法：语言无关的词嵌入和语言对齐的词嵌入。这两种方法都可以用来引导一种新语言的社交媒体消息的分类器，只有很少或没有标记数据。最后，我们描述了一种方法，用于选择相关的和代表性的消息，并显示他们在界面上的EFAS。
This paper describes a prototype system that integrates social media analysis into the European Flood Awareness System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and representative messages and displaying them back in the interface of EFAS.