论文标题
使用基于BERT的语言模型的灾难推文分类
Disaster Tweets Classification using BERT-Based Language Model
论文作者
论文摘要
在紧急情况下，社交网络服务已成为一个重要的沟通渠道。这项研究的目的是创建一个机器学习语言模型，该模型能够调查一个人或地区是否处于危险之中。智能手机的无处不在，使人们能够实时宣布他们正在观察的紧急情况。因此，越来越多的机构有兴趣通过编程监视Twitter（即救灾组织和新闻机构）。设计一种能够理解并确认何时基于社交网络帖子发生灾难的语言模型将随着时间的流逝而变得越来越必要。
Social networking services have became an important communication channel in time of emergency. The aim of this study is to create a machine learning language model that is able to investigate if a person or area was in danger or not. The ubiquitousness of smartphones enables people to announce an emergency they are observing in real-time. Because of this, more agencies are interested in programmatically monitoring Twitter (i.e. disaster relief organizations and news agencies). Design a language model that is able to understand and acknowledge when a disaster is happening based on the social network posts will become more and more necessary over time.
