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Televised Ebola news coverage influences social media panic
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Published data collected from Internet searches and Twitter feeds suggests a disproportionate amount of online panic concerning the recent Ebola outbreak was fostered by televised media reports.
“Social media data have been suggested as a way to track the spread of a disease in a population, but there is a problem that in an emerging outbreak people also use social media to express concern about the situation,” Sherry Towers, PhD, of Arizona State University’s Simon A. Levin Mathematical, Computational and Modeling Sciences Center, said in a press release. “It is hard to separate the two effects in a real outbreak situation.”
Towers and colleagues examined daily Google search data and Twitter data in the United States during a 6-week period ending in Oct. 31, 2014, along with television news coverage quantified by the number of Ebola-related news videos appearing on two major networks.
Google Trends was used to assess Ebola-related Google searches, with terms that included “Ebola symptoms” and “Do I have Ebola?” Likewise, the researchers identified tweets using the keywords “Ebola” or “symptoms,” excluding tweets by known news organizations to avoid possible bias. The researchers used videos organized by date from MSNBC and Fox News as a proxy for chronological trends in the amount of news coverage pertaining to Ebola. The researchers fit the parameters of a mathematical model of contagion to ascertain whether “news media contagion” played a significant role in time trends of Ebola-associated Google searches and tweets.
Using this model, the researchers determined that each Ebola-related news video prompted tens of thousands of Ebola-associated tweets and Internet searches, and that the model delineated between 65% and 76% of the variance in all samples.
“When we compared the temporal patterns in these data to the patterns in the number of Ebola-related news stories that ran on major news networks, we found that the peaks and valleys in both almost exactly matched,” Carlos Castillo-Chavez, PhD, a mathematical epidemiologist at Arizona State’s School of Human Evolution and Social Change, said in the release. “We were amazed at how incredibly similar the temporal patterns were.”
Moreover, the researchers identified a “boredom effect,” in which a sustained period of Ebola news coverage had had an attenuating effect on Ebola-related searches and tweets.
“We have explored a source of major potential bias when applying digital epidemiological methodology to emerging disease outbreaks,” the researchers wrote. “While media-induced panic is certainly not the only source of bias in such situations, we hope the results of our study will be informative for future analyses.”
Disclosure: The researchers report no relevant financial disclosures.
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