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Mass Media and the Contagion of Fear: The Case of Ebola in America.

Towers S, Afzal S, Bernal G, Bliss N, Brown S, Espinoza B, Jackson J, Judson-Garcia J, Khan M, Lin M, Mamada R, Moreno VM, Nazari F, Okuneye K, Ross ML, Rodriguez C, Medlock J, Ebert D, Castillo-Chavez C - PLoS ONE (2015)

Bottom Line: 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.Between 65% to 76% of the variance in all samples is described by the news media contagion model.

View Article: PubMed Central - PubMed

Affiliation: Arizona State University, Tempe, AZ, U. S. A.

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.

No MeSH data available.


Related in: MedlinePlus

Time series of Ebola-related news media, Twitter, and Google search data used in this study.The samples consist of six weeks of data ending October 31st, 2014. The first case of Ebola confirmed in the U. S. occurred on September 29, 2014. The temporal trends in the data samples are highly inter-correlated, with a minimum of 70% correlation between samples.
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pone.0129179.g002: Time series of Ebola-related news media, Twitter, and Google search data used in this study.The samples consist of six weeks of data ending October 31st, 2014. The first case of Ebola confirmed in the U. S. occurred on September 29, 2014. The temporal trends in the data samples are highly inter-correlated, with a minimum of 70% correlation between samples.

Mentions: The data are shown in Fig 2.


Mass Media and the Contagion of Fear: The Case of Ebola in America.

Towers S, Afzal S, Bernal G, Bliss N, Brown S, Espinoza B, Jackson J, Judson-Garcia J, Khan M, Lin M, Mamada R, Moreno VM, Nazari F, Okuneye K, Ross ML, Rodriguez C, Medlock J, Ebert D, Castillo-Chavez C - PLoS ONE (2015)

Time series of Ebola-related news media, Twitter, and Google search data used in this study.The samples consist of six weeks of data ending October 31st, 2014. The first case of Ebola confirmed in the U. S. occurred on September 29, 2014. The temporal trends in the data samples are highly inter-correlated, with a minimum of 70% correlation between samples.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4465830&req=5

pone.0129179.g002: Time series of Ebola-related news media, Twitter, and Google search data used in this study.The samples consist of six weeks of data ending October 31st, 2014. The first case of Ebola confirmed in the U. S. occurred on September 29, 2014. The temporal trends in the data samples are highly inter-correlated, with a minimum of 70% correlation between samples.
Mentions: The data are shown in Fig 2.

Bottom Line: 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.Between 65% to 76% of the variance in all samples is described by the news media contagion model.

View Article: PubMed Central - PubMed

Affiliation: Arizona State University, Tempe, AZ, U. S. A.

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.

No MeSH data available.


Related in: MedlinePlus