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Quantifying Network Dynamics and Information Flow Across Chinese Social Media During the African Ebola Outbreak

Published online by Cambridge University Press:  01 August 2017

Shihui Feng ,
Liaquat Hossain Open the ORCID record for Liaquat Hossain [Opens in a new window] ,
John W. Crawford  and
Terry Bossomaier
Shihui Feng
Affiliation:
Information Management, Division of Information and Technology Studies, The University of Hong Kong, Hong Kong
Liaquat Hossain*
Affiliation:
Library and Information Management Program, Division of Information and Technology Studies, The University of Hong Kong, Hong Kong
John W. Crawford
Affiliation:
Rothamsted Research, Harpenden, United Kingdom
Terry Bossomaier
Affiliation:
Faculty of Business, Charles Sturt University, Albury, Australia
*
Correspondence and reprint requests to Liaquat Hossain, PhD, Professor of Library and Information Management, Division of Information and Technology Studies, Room 113, Runme Shaw Building, The University of Hong Kong, Pokfulam Road, Hong Kong (e-mail: [email protected]).
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Abstract

Objective

Social media provides us with a new platform on which to explore how the public responds to disasters and, of particular importance, how they respond to the emergence of infectious diseases such as Ebola. Provided it is appropriately informed, social media offers a potentially powerful means of supporting both early detection and effective containment of communicable diseases, which is essential for improving disaster medicine and public health preparedness.

Methods

The 2014 West African Ebola outbreak is a particularly relevant contemporary case study on account of the large number of annual arrivals from Africa, including Chinese employees engaged in projects in Africa. Weibo (Weibo Corp, Beijing, China) is China’s most popular social media platform, with more than 2 billion users and over 300 million daily posts, and offers great opportunity to monitor early detection and promotion of public health awareness.

Results

We present a proof-of-concept study of a subset of Weibo posts during the outbreak demonstrating potential and identifying priorities for improving the efficacy and accuracy of information dissemination. We quantify the evolution of the social network topology within Weibo relating to the efficacy of information sharing.

Conclusions

We show how relatively few nodes in the network can have a dominant influence over both the quality and quantity of the information shared. These findings make an important contribution to disaster medicine and public health preparedness from theoretical and methodological perspectives for dealing with epidemics. (Disaster Med Public Health Preparedness. 2018;12:26–37)

Keywords

network dynamicsinformation flowsocial mediaEbola outbreak
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 12 , Issue 1 , February 2018 , pp. 26 - 37
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2017 

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