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Building Intelligent Indicators to Detect Dengue Epidemics in Brazil using Social Networks

机译:使用社交网络建立智能指标以检测巴西的登革热流行

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The area of Text Mining has an increasing growing with the support of Machine Learning techniques. Nowadays, the quantity of available data is bigger than the last years. Among the various sources of information, social networks have been highlighted, since they can be used in the extraction of relevant information using posts, tweets and comments as basis. In this work, the social network used is Twitter. Many works explores Twitter platform to get tweets and analyze them to detect social events. This identification is possible due to the users are considered sensors. Consequently, they express their feelings and considerations from external stimuli. The combination of the information and machine learning algorithms makes possible the identification and the monitoring interest events. This work analyzes tweets from Brazil to detect dengue in such country. The results show the utility of the proposal to recognize dengue epidemics in the Brazilian territory.
机译:在机器学习技术的支持下,文本挖掘的领域正在不断增长。如今,可用数据量比过去几年要多。在各种信息来源中,社交网络已得到强调,因为它们可以以帖子,推文和评论为基础用于提取相关信息。在这项工作中,使用的社交网络是Twitter。许多作品探索Twitter平台以获取推文并对其进行分析以检测社交事件。由于用户被认为是传感器,因此这种识别是可能的。因此,他们通过外部刺激表达了自己的感受和考虑。信息和机器学习算法的结合使识别和监视兴趣事件成为可能。这项工作分析了来自巴西的推文,以发现该国的登革热。结果表明,该提案可用于识别巴西境内的登革热流行。

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