This study aimed to analyze main groups accused on social media of causing or spreading the 2014-2016 Ebola epidemic in West Africa. In this analysis, blame is construed as a vehicle of meaning through which the lay public makes sense of an epidemic, and through which certain classes of people become ''figures of blame''. Data was collected from Twitter and Facebook using key word extraction, then categorized thematically. Our findings indicate an overall proximate blame tendency: blame was typically cast on ''near-by'' figures, namely national governments, and less so on ''distant'' figures, such as generalized figures of otherness (''Africans'', global health authorities, global elites). Our results also suggest an evolution of online blame. In the early stage of the epidemic, blame directed at the affected populations was more prominent. However, during the peak of the outbreak, the increasingly perceived threat of inter-continental spread was accompanied by a progressively proximal blame tendency, directed at figures with whom the social media users had pre-existing biopolitical frustrations. Our study proposes that pro-active and on-going analysis of blame circulating in social media can usefully help to guide communications strategies, making them more responsive to public perceptions.

This study of comments posted on major French print and TV media websites during the H1N1 epidemic illustrates the relationship between the traditional media and social media in responding to an emerging disease. A disturbing "geography of blame" was observed suggesting the metamorphosis of the folk-devil phenomenon to the Internet. We discovered a subterranean discourse about the putative origins and "objectives" of the H1N1 virus, which was absent from the discussions in mainstream television channels and large-circulation print media. These online rumours attributed hidden motives to governments, pharmaceutical companies, and figures of Otherness that were scapegoated in the social history of previous European epidemics, notably Freemasons and Jews.

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Introduction: The 2013-2015 outbreak of Ebola was by far the largest to date, affecting Guinea, Liberia, Sierra Leone, and secondarily, Nigeria, Senegal and the United States. Such an event raises questions about the circulation of health information across social networks. This article presents an analysis of tweets concerning a specific theme: the sexual transmission of the virus by survivors, at a time when there was a great uncertainty about the duration and even the possibility of such transmission.Methods: This article combines quantitative and qualitative analysis. From a sample of 50,000 tweets containing the words “Ebola” in French and English, posted between March 15 and November 8, 2014, we created a graphic representation of the number of tweets over time, and identified two peaks: the first between July 27 and August 16, 2014 (633 tweets) and the second between September 28 and November 8, 2014 (2,577 tweets). This sample was divided into two parts, and every accessible publication was analyzed and coded according to the authors’ objectives, feelings expressed and/or publication type.Results: While the results confirm the significant role played by mainstream media in disseminating information, media did not create the debate around the sexual transmission of Ebola and Twitter does not fully reflect mainstream media contents. Social media rather work like a “filter”: in the case of Ebola, Twitter preceded and amplified the debate with focusing more than the mainstream media on the sexual transmission, as expressed in jokes, questions and criticism.Discussion: Online debates can of course feed on journalistic or official information, but they also show great autonomy, tinged with emotions or criticisms. Although numerous studies have shown how this can lead to rumors and disinformation, our research suggests that this relative autonomy makes it possible for Twitter users to bring into the public sphere some types of information that have not been widely addressed. Our results encourage further research to understand how this “filter” works during health crises, with the potential to help public health authorities to adjust official communications accordingly. Without a doubt, the health authorities would be well advised to put in place a special watch on the comments circulating on social media (in addition to that used by the health monitoring agencies).