Arabic Event Detection in Social Media
作者： Nasser Alsaedi , Pete Burnap
DOI: 10.1007/978-3-319-18111-0_29
关键词: Social media 、 Naive Bayes classifier 、 Data collection 、 Cluster analysis 、 World Wide Web 、 Computer science 、 Automatic summarization 、 Data science 、 Web application 、 Information extraction 、 Event (computing)
摘要: Event detection is a concept that crucial to the assurance of public safety surrounding real-world events. Decision makers use information from range terrestrial and online sources help inform decisions enable them develop policies react appropriately events as they unfold. One such source social media. Twitter, form media, popular micro-blogging web application serving hundreds millions users. User-generated content can be utilized rich identify In this paper, we present novel framework for identifying events, with focus on ‘disruptive’ using Twitter data.The approach based five steps; data collection, pre-processing, classification, clustering summarization. We Naive Bayes classification model an Online Clustering method validate our over multiple sets. To best knowledge, study first effort in Arabic
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sci-hub.st 参考文章(26)
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