Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis.

J Danielle Sharpe Richard S Hopkins Robert L Cook Catherine Woodstock Striley

Published in: JMIR public health and surveillance (2016)

Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed.

Keyphrases

electronic health record
big data
social media
public health
drinking water
cell cycle
machine learning
cell proliferation