The Spread and Mutation of Science Misinformation
The Spread and Mutation of Science Misinformation
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科学错误信息的传播和变异
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Ania Korsunska
中科院分区：
文献类型：
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作者：
Ania Korsunska
随着媒体环境向数字化转变，我们看到创建、管理和纠正信息的角色从专业的“看门人”记者转向更广泛的媒体行业和公众。这种转变导致了错误信息的传播。虽然政治“假新闻”是目前一个热门的研究领域，但本研究调查了另一个相关现象：科学误导。事实证明，持续接触科学错误信息会培养对疾病风险、原因和患病率的错误信念，并使公众失去改变健康生活方式的动力。尽管需要更多的研究，科学错误信息传播的研究是稀缺的。通过一个案例研究，跟踪通过超链接引用一个特定的文章的信息传播，本研究增加了有价值的见解媒体网络的内部运作，概念化的错误信息传播和方法论的方法，多平台的错误信息跟踪。案例研究说明了媒体来源对二手信息的过度依赖以及不断变化的在线内容的新现象。最初的错误信息提供者能够删除误导性信息，因此，所有后续文章最终都会将错误信息引用到一个不再存在的来源。这种在线更新内容的能力打破了信息流的过程：新闻故事不再代表时间的快照，而是活的、变异的有机体，使任何对媒体网络的研究变得越来越复杂。
As the media environment has shifted towards digitization, we have seen the roles of creating, curating and correcting information shift from professional “gatekeeper” journalists to a broader media industry and the general public. This shift has led to the spread of misinformation. Though political “fake news” is currently a popular area of study, this study investigates another related phenomenon: science misinformation. Consistent exposure to science misinformation has been shown to cultivate false beliefs about risks, causes and prevalence of illnesses and disincentivize the public from implementing healthy lifestyle changes. Despite the need for more research, science misinformation dissemination studies are scarce. Through a case study that traces the spread of information about one specific article through hyperlink citations, this study adds valuable insights into the inner workings of media networks, conceptualizations of misinformation spread and methodological approaches to multi-platform misinformation tracing. The case study illustrates the over-reliance of media sources on secondary information and the novel phenomenon of constantly mutating online content. The original misinformant is able to remove misleading information, and as a result, all of the subsequent articles end up referencing misinformation to a source that no longer exists. This ability to update content online breaks the information flow process: news stories no longer represent a snapshot in time but instead living, mutating organisms, making any study of media networks increasingly complex.