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Towers, Sherry
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Afzal, Shehzad
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Bernal, Gilbert
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Bliss, Nadya
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Brown, Shala
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Espinoza, Baltazar
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Jackson, Jasmine
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Judson-Garcia, Julia
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Khan, Maryam
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Lin, Michael
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Mamada, Robert
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Moreno, Victor M.
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Nazari, Fereshteh
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Okuneye, Kamaldeen
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Ross, Mary L.
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Rodriguez, Claudia
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Medlock, Jan
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Ebert, David
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Castillo-Chavez, Carlos
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| Abstract |
- Background
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends. Methodology:
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions:
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
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| Citation |
- Towers, S., Afzal, S., Bernal, G., Bliss, N., Brown, S., Espinoza, B., ... & Castillo-Chavez, C. (2015). Mass media and the contagion of fear: the case of ebola in America. PLoS ONE, 10(6), e0129179. doi:10.1371/journal.pone.0129179
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| Funding Statement (additional comments about funding) |
- The parameter optimization portion of the analysis was made possible with education allocation #DMS140043 of super-computing resources from National Science Foundation Extreme Science and Engineering Discovery Environment (XSEDE) high-performance computing initiative (ST GB NB SB BE JJ JJG MK ML RM VMM FN KO MLR CR CCC). This research was also partially supported by the Western Alliance to Expand Student Opportunities (WAESO) Louis Stokes Alliance for Minority Participation (LSAMP) Bridge to the Doctorate (BD) National Science Foundation (NSF) "Multidisciplinary STEM Solutions LSAMP Bridge to the Doctorate" grant #HRD-1401190 (GB SB JJ JJG MLR CR), and the Offices of the President and Provost of Arizona State University. This work was funded in part by the U.S. Department of Homeland Security (DHS) VACCINE Center award #2009-ST-061-CI0001-06 (SA DE), and was also made possible by grant #1R01GM100471-01 from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health (CCC).
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