Fire disaster awareness based on microblog messages using Naïve bayes algorithm and key-code language detection technique

Zhao Ming, R. Ganiyu
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Abstract

In recent years, social media has been an efficient platform for fast dissemination of information. The advent of microblogs however boost disaster awareness immensely as many researchers dive into actively analyzing short messages from various internet users around the globe. Our algorithm hereby employs a method in which Naïve Bayes algorithm was adopted to analyze microblog messages for fire disaster awareness. We also device a language detection algorithm which could overcome language barriers in processing microblog messages extensively. Weibo data of year 2012 was experimented on and an accuracy between 87% and 99% was obtained.
基于Naïve贝叶斯算法和密钥码语言检测技术的微博信息火灾感知
近年来,社交媒体已经成为信息快速传播的有效平台。然而,微博的出现极大地提高了人们的灾难意识,因为许多研究人员都在积极地分析来自全球不同互联网用户的短信。本文算法采用Naïve贝叶斯算法对微博消息进行火灾感知分析。我们还设计了一种语言检测算法,可以克服微博信息处理中的语言障碍。对2012年的微博数据进行实验,准确率在87% ~ 99%之间。
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