Network based model of social media big data predicts contagious disease diffusion
Abstract
Purpose
Predicting future outbreaks and understanding how they are spreading from location to location can improve patient care provided. Recently, mining social media big data provided the ability to track patterns and trends across the world. This study aims to analyze social media micro-blogs and geographical locations to understand how disease outbreaks spread over geographies and to enhance forecasting of future disease outbreaks.
Design/methodology/approach
In this paper, the authors use Twitter data as the social media data source, influenza-like illnesses (ILI) as disease epidemic and states in the USA as geographical locations. They present a novel network-based model to make predictions about the spread of diseases a week in advance utilizing social media big data.
Findings
The authors showed that flu-related tweets align well with ILI data from the Centers for Disease Control and Prevention (CDC) (p < 0.049). The authors compared this model to earlier approaches that utilized airline traffic, and showed that ILI activity estimates of their model were more accurate. They also found that their disease diffusion model yielded accurate predictions for upcoming ILI activity (p < 0.04), and they predicted the diffusion of flu across states based on geographical surroundings at 76 per cent accuracy. The equations and procedures can be translated to apply to any social media data, other contagious diseases and geographies to mine large data sets.
Originality/value
First, while extensive work has been presented utilizing time-series analysis on single geographies, or post-analysis of highly contagious diseases, no previous work has provided a generalized solution to identify how contagious diseases diffuse across geographies, such as states in the USA. Secondly, due to nature of the social media data, various statistical models have been extensively used to address these problems.
Keywords
Acknowledgements
The authors would like to thank David Wise for thoughtful discussions and bringing this problem to our attention. This research was partially supported by a Grant from NIH/NCRR CTSA KL2TR000440 to GB.
Citation
Elkin, L.S., Topal, K. and Bebek, G. (2017), "Network based model of social media big data predicts contagious disease diffusion", Information Discovery and Delivery, Vol. 45 No. 3, pp. 110-120. https://doi.org/10.1108/IDD-05-2017-0046
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited