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.

中文翻译：

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埃博拉和社交媒体的局部指责：2014-2015 年埃博拉疫情期间 Twitter 和 Facebook 对话分析。

这项研究旨在分析社交媒体上被指控造成或传播2014-2016年西非埃博拉疫情的主要群体。在这种分析中，指责被解释为一种意义的载体，通过它，普通公众可以理解流行病，并且通过它，某些阶层的人成为“指责对象”。使用关键词提取从 Twitter 和 Facebook 收集数据，然后按主题分类。我们的研究结果表明了总体上的直接指责倾向：指责通常集中在“附近”的人物，即国家政府，而不是“遥远”的人物，例如普遍的其他人物（“非洲人”，全球卫生当局，全球精英）。我们的结果还表明网上指责的演变。疫情初期，针对受影响人群的指责更为突出。然而，在疫情爆发的高峰期，人们越来越意识到洲际传播的威胁，同时也伴随着越来越近端的指责倾向，矛头指向社交媒体用户先前存在的生物政治挫败感的人物。我们的研究表明，对社交媒体中传播的指责进行主动和持续的分析可以有效地帮助指导沟通策略，使它们更能响应公众的看法。