Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification

作者：

Highlights：

• End to End software system built with open source tools for real-time processing of public social media data.

• Event detection and Situational Awareness of disease outbreaks.

• Development of a classifier for isolating health-related tweets using deep neural networks.

• Nowcasting for multiple diseases based on the syndromic surveillance data.

摘要

•End to End software system built with open source tools for real-time processing of public social media data.•Event detection and Situational Awareness of disease outbreaks.•Development of a classifier for isolating health-related tweets using deep neural networks.•Nowcasting for multiple diseases based on the syndromic surveillance data.

论文关键词：Real-time processing,Classification,Clustering,Event detection,68T50,68T05,62M20

论文评审过程：Received 31 May 2017, Revised 31 January 2018, Accepted 28 April 2018, Available online 1 June 2018, Version of Record 7 March 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2018.04.011