Inferring the origin locations of tweets with quantitative confidence
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Recent work in machine learning and natural language processing has studied the health content of tweets and demonstrated the potential for extracting useful public health information from their aggrega-tion. This article examines the types of health topics discussed on Twitter, and how tweets can both augment existing public health capabilities and enable new ones. The author also discusses key chal-lenges that researchers must address to deliver high-quality tools to the public health community.