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首页> 外文会议>9th International conference on language resources and evaluation >A Framework for Public Health Surveillance
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A Framework for Public Health Surveillance

机译：公共卫生监测框架

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With the rapid growth of social media, there is increasing potential to augment traditional public health surveillance methods with data from social media. We describe a framework for performing public health surveillance on Twitter data. Our framework, which is publicly available, consists of three components that work together to detect health-related trends in social media: a concept extraction component for identifying health-related concepts, a concept aggregation component for identifying how the extracted health-related concepts relate to each other, and a trend detection component for determining when the aggregated health-related concepts are trending. We describe the architecture of the framework and several components that have been implemented in the framework, identify other components that could be used with the framework, and evaluate our framework on approximately 1.5 years of tweets. While it is difficult to determine how accurately a Twitter trend reflects a trend in the real world, we discuss the differences in trends detected by several different methods and compare flu trends detected by our framework to data from Google Flu Trends.
机译：随着社交媒体的快速增长，增加了社交媒体数据的传统公共卫生监测方法的潜力。我们描述了对Twitter数据进行公共卫生监控的框架。我们公开可用的框架包括三个组件，共同讨论社交媒体中的健康相关趋势：识别与识别健康相关概念的概念提取组件，是识别提取的健康有关概念的概念聚合组成部分彼此，以及用于确定汇总的健康相关概念何时何种趋势的趋势检测组件。我们描述了框架的架构和在框架中实现的多个组件，识别可以与框架一起使用的其他组件，并在大约1.5年的推文上评估我们的框架。虽然很难确定推特趋势的准确程度反映了现实世界的趋势，但我们讨论了几种不同方法检测到的趋势的差异，并比较了我们框架与谷歌流感趋势的数据检测到的流感趋势。

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