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首页> 外文会议>Proceedings of the Twenty-Third international joint conference on artificial intelligence >Detecting and Tracking Disease Outbreaks by Mining Social Media Data
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Detecting and Tracking Disease Outbreaks by Mining Social Media Data

机译：通过挖掘社交媒体数据检测和跟踪疾病暴发

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摘要

The emergence and ubiquity of online social networks have enriched web data with evolving interactions and communities both at mega-scale and in real-time.This data offers an unprecedented opportunity for studying the interaction between society and disease outbreaks.The challenge we describe in this data paper is how to extract and leverage epidemic outbreak insights from massive amounts of social media data and how this exercise can benefit medical professionals,patients,and policymakers alike.We attempt to prepare the research community for this challenge with four datasets.Publishing the four datasets will commoditize the data infrastructure to allow a higher and more efficient focal point for the research community.
机译：在线社交网络的出现和普及，通过大规模和实时的不断发展的互动和社区丰富了网络数据，这些数据为研究社会与疾病暴发之间的互动提供了前所未有的机会。数据纸是如何从大量社交媒体数据中提取和利用流行病爆发的见解，以及这种做法如何使医疗专业人员，患者和政策制定者都受益。我们尝试通过四个数据集为研究社区做好准备，以应对这一挑战。数据集将使数据基础设施商品化，从而为研究界提供更高，更高效的焦点。

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