How Did Ebola Information Spread on Twitter?
Document Type
Presentation
Presentation Date
8-23-2016
Abstract or Description
Theoretical Background and Research Questions/Hypothesis: Social networks are beneficial for the communications of public health information. In the pre-Internet age, large-scale dissemination of health information relied on mass media broadcasts. The importance of interpersonal communication has been celebrated in the age of social media. The interpersonal transmission of online messages could be analogous to the spread of the infectious diseases, and such type of information diffusion is referred as the viral spreading mechanism. The primary purpose of this project is to examine whether the traditional broadcast mechanism or the viral spreading mechanism dominated the Ebola information diffusion on Twitter. Lessons learned can then contribute towards developing more effective communication strategies.
Methods: Our data was purchased from GNIP, the official Twitter data provider. We obtained all Ebola-related tweets (including retweets and replies) posted from March 23, 2014 to May 31, 2015. We reconstructed the Ebola retweeting paths based on Twitter contents and the following relationships. Social network analysis was performed to investigate the retweeting patterns.
Results:On average, 91% of the retweets were directly retweeted from the initial tweeters. On average, the maximum number of steps of information transmission between retweeters and the initial tweeters was 3, i.e. Initial user -> Follower -> Follower -> Follower. These observations suggested that large viral networks were uncommon and broadcast spreading was more pervasive than viral spreading for Ebola-related tweets. According to the retweeting and following relationships, four types of initial users were identified: "broadcasters" (38%), "common users" (60%), "influentials" (2%), and "hidden influentials" (
Conclusions: Broadcast spreading was the dominant mechanism (vs. viral spreading) for infectious disease outbreak-related (e.g., Ebola) information on Twitter, and it could lead to large scale dissemination.
Implications for Research and/or Practice: Unlike social networks with viral spreading, the initial tweeters (i.e., sources of information) and their messages are much more important than common users if the broadcast spreading mechanism is dominant. Therefore, as far as Ebola health communication was concerned, "influential" or "hidden influential" sources (e.g., social media accounts operated by traditional mass media) would be important partners to disseminate Ebola-related health information.
Sponsorship/Conference/Institution
National Conference on Health Communication, Marketing, and Media (NCHCMM)
Location
Atlanta, GA
Recommended Citation
Liang, Hai, Isaac Chun-Hai Fung, Zion Tsz Ho Tse, Jingjing Yin, Chung-Hong Chan, L. Pechta, B. Smith, Rolando J. Marquez, Martin Meltzer, K. Lubell, King-Wa Fu.
2016.
"How Did Ebola Information Spread on Twitter?."
Biostatistics Faculty Presentations.
Presentation 100.
https://digitalcommons.georgiasouthern.edu/biostat-facpres/100
