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

Towers, Sherry; Afzal, Shehzad; Bernal, Gilbert; Bliss, Nadya; Brown, Shala; Espinoza, Baltazar; Jackson, Jasmine; Judson-Garcia, Julia; Khan, M. Laeeq; Lin, Michael; Mamada, Robert; Moreno, V.M.; Nazari, Fereshteh; Okuneye, Kamaldeen; Ross, Mary L.; Rodríguez, Claudia; Medlock, Jan; Ebert, David S.; Castillo‐Chavez, Carlos

doi:10.1371/journal.pone.0129179

Cited by 195 publications

(154 citation statements)

References 32 publications

(25 reference statements)

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“…Like other studies of Western news outlets, 6 we found that articles in the GM provided unbalanced and somewhat sensationalist coverage of the 2014 Ebola outbreak and its risks. The GM highlighted matters of security, humanitarianism and economics.…”

Section: Discussionsupporting

confidence: 76%

“…This outbreak, 3 the largest since the Ebola virus was discovered in 1976, 1 attracted significant media attention. 4,5 Studies have explored coverage of the 2014 Ebola outbreak in media outlets such as Twitter, 6 Google, 4 YouTube 7 and print news media. 5,8 In a quantitative analysis of 301 articles published in three leading US newspapers, the most common topic was cases in the United States (39.0%), followed by the outbreak in West Africa (33.6%).…”

mentioning

confidence: 99%

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Comparing “insider” and “outsider” news coverage of the 2014 Ebola outbreak

Humphries

Radice

Lauzier

2017

Can J Public Health

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OBJECTIVES: Information provided by news media during an infectious disease outbreak can affect the actions taken to safeguard public health. There has been little evaluation of how the content of news published during an outbreak varies by location of the news outlet. This study analyzes coverage of the 2014 Ebola outbreak by one news outlet operating within a country affected by the outbreak and one country not directly affected.

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Section: Discussionsupporting

confidence: 76%

mentioning

confidence: 99%

Comparing “insider” and “outsider” news coverage of the 2014 Ebola outbreak

Humphries

Radice

Lauzier

2017

Can J Public Health

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“…Ripples were felt across the world in a contagion of fear and global panic 1 -with effects extending as far as the USA 2 where it influenced voter behaviour. The disease ravaged Sierra Leone, Liberia, Guinea and Mali, all sharing land borders, on a scale never experienced before and was transmitted by air travel to Nigeria.…”

Section: Introductionmentioning

confidence: 99%

Scientific and non-scientific information in the uptake of health information: The case of Ebola

Falade¹,

Coultas²

2017

S. Afr. J. Sci.

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The Ebola virus disease outbreak in West Africa (2013–2016) claimed over 10 000 lives in less than 18 months. Low levels of familiarity with the disease, ease of transmission, scale of infection, gruesomeness of symptoms, lack of cure and high fatality rate created a global panic. From the perspective of the social psychology of communication and content analysis, this study examines media coverage of the crisis in Africa with a view to unpacking the scientific and non-scientific information that may have framed public understanding of the disease. Findings show that accepting scientific advice was not unproblematic, because of the similarity of early symptoms with known diseases such as Lassa, dengue and malaria fevers. Cultural and religious actors and beliefs posed a paradox for believers as the public assimilated disease prevention information into existing norms and practices. Rumours and conspiracy theories about Western governments and pharmaceuticals also contributed to the rejection of the scientific explanation of its origin. Fear of the devastating effects of the disease and the lack of a cure led to the stigmatisation of the infected and treatment centres and ultimately to public revolts. Findings show the importance of non-scientific information and actors in matters of health and illness in Africa.

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“…The outbreak of Ebola in West Africa in 2014 received a disproportionate amount of media coverage and public attention relative to the threat it posed to public health in the United States [1,2]. Mathematical models at the aggregate level have been proposed to explain the contagion process of information on social media [1].…”

Section: Introductionmentioning

confidence: 99%

“…Mathematical models at the aggregate level have been proposed to explain the contagion process of information on social media [1]. However, a more fundamental question remains unknown-how did Ebola messages diffuse on social media platforms?…”

Section: Introductionmentioning

confidence: 99%

How did Ebola Information Spread on Twitter: Broadcasting or Viral Spreading? (Preprint)

Liang¹,

Fung²,

Tse³

et al. 2018

Preprint

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Background: It has been argued that information and emotions towards public health issues could spread widely through online social networks. Although aggregate metrics on the volume of information diffusion are available, we know little about how information spreads on online social networks. For example, health information could be transmitted from one to many (i.e. broadcasting), which is similar to how traditional mass media passes information to the general public. Health information could also be transmitted from many to many (i.e. viral spreading), which is analogous to the spread of infectious diseases. Objective: The aim of this study is to determine the spreading pattern of Ebola information on Twitter and identify influential users regarding Ebola messages. On Twitter, influential users are those whose tweets receive a large number of retweets. 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 Ebola-related retweeting paths based on Twitter content and the follower-followee relationships (who follows whom on Twitter). Social network analysis was performed to investigate retweeting patterns. In addition to describing the diffusion structures, we classify users in the network into four categories (i.e., influential user, hidden influential user, disseminator, common user) based on following and retweeting patterns. Disseminators received fewer retweets than expected based on their number of followers, common users and influential users received as many or fewer retweets than expected, and hidden influential users received more retweets than expected. Results: On average, 91% of the retweets were directly retweeted from the initial message. Moreover, 47.5% of the retweeting paths of the original tweets had a depth of 1 (i.e., from the seed user to its immediate followers). These observations suggested that the broadcast model was more pervasive than viral spreading. Furthermore, we found that influential users and hidden influential users can trigger more retweets than disseminators and common users. Disseminators and common users relied more on the viral model for spreading information beyond their immediate followers via influential and hidden influential users. Conclusions: The broadcast model was the dominant mechanism of information diffusion of a major health event on Twitter. It suggests that public health communicators can work with influential and hidden influential users to get the message across, because influential and hidden influential users can reach more people that are not following the public health Twitter accounts. Although both influential users and hidden influential users can trigger a lot of retweets, recognizing and using the hidden influential users as the source of information could potentially be a cost-effective communication strategy for public health promotion, because the hidden influential users can receive...

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

Cited by 195 publications

References 32 publications

Comparing “insider” and “outsider” news coverage of the 2014 Ebola outbreak

Comparing “insider” and “outsider” news coverage of the 2014 Ebola outbreak

Scientific and non-scientific information in the uptake of health information: The case of Ebola

How did Ebola Information Spread on Twitter: Broadcasting or Viral Spreading? (Preprint)

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