Classification of Social Media Messages Posted at the Time of Disaster
作者： Kemachart Kemavuthanon , Osamu Uchida
DOI: 10.1007/978-3-030-48939-7_18
关键词: Process (engineering) 、 Ontology (information science) 、 Word (computer architecture) 、 Similarity (psychology) 、 Social media 、 Computer science 、 World Wide Web 、 Social relation
摘要: Nowadays, social media is one of the essential sharing information and proliferation tools because it spreads text messages, news, pictures, or videos in real-time. During disaster, Japanese people use to exchange real-time for their interaction. Twitter most popular tool that has been used disaster response Japan. Even though many systems have created mitigation Japan, them are assumed be by language. From this problem, study focuses on way create a system community service help, collect, extract help becomes more important. This paper aims investigate tweets focusing noun keywords during Osaka North Earthquake 18 June 2018 with data set than 9,000,000 tweets. The process presented classify messages using ontology, word similarity, frequency keyword, evaluate results natural language processing. We organize into 15 categories as classification algorithms machine learning features count each category sentences. result were statistically compared keyword content collecting build analysis system.
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