Literature DB >> 28760166

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

Shihui Feng1, Liaquat Hossain2, John W Crawford3, Terry Bossomaier4.   

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).

Entities:  

Keywords:  Ebola outbreak; information flow; network dynamics; social media

Mesh:

Year:  2017        PMID: 28760166     DOI: 10.1017/dmp.2017.29

Source DB:  PubMed          Journal:  Disaster Med Public Health Prep        ISSN: 1935-7893            Impact factor:   1.385


  4 in total

1.  Microblog data analysis of emotional reactions to COVID-19 in China.

Authors:  Yuchang Jin; Aoxue Yan; Tengwei Sun; Peixuan Zheng; Junxiu An
Journal:  J Psychosom Res       Date:  2022-06-30       Impact factor: 4.620

2.  Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts.

Authors:  Chunmei Huang; Xinjie Xu; Yuyang Cai; Qinmin Ge; Guangwang Zeng; Xiaopan Li; Weide Zhang; Chen Ji; Ling Yang
Journal:  J Med Internet Res       Date:  2020-05-17       Impact factor: 5.428

3.  Chinese Public's Attention to the COVID-19 Epidemic on Social Media: Observational Descriptive Study.

Authors:  Yuxin Zhao; Sixiang Cheng; Xiaoyan Yu; Huilan Xu
Journal:  J Med Internet Res       Date:  2020-05-04       Impact factor: 5.428

4.  Analysis of the Evolution of User Emotion and Opinion Leaders' Information Dissemination Behavior in the Knowledge Q&A Community during COVID-19.

Authors:  Xu Xu; Zhigang Li; Rui Wang; Li Zhao
Journal:  Int J Environ Res Public Health       Date:  2021-11-22       Impact factor: 3.390

  4 in total

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