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

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.

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.

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.

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).