超越 (错误) 陈述:COVID-19错误信息中的视觉效果
J Scott Brennen1, Felix M Simon1, Rasmus Kleis Nielsen1
1University of Oxford, Oxford, UK.
概括
这项研究分析了COVID-19错误信息中的视觉效果,发现它们经常作为虚假声明的证据. 大多数视觉内容被错误标记,而不是人工智能生成的深度假冒,突出了在健康错误信息中分析视觉内容的必要性.
科学领域:
- 医学视觉沟通 医学视觉沟通
- 数字健康错误信息分析分析
- 信息科学 信息科学 信息科学
背景情况:
- 视觉信息越来越多地用于健康错误信息,特别是在COVID-19方面.
- 了解这些视觉效果的作用和功能对于打击虚假叙述至关重要.
- 现有的研究往往忽略了在错误信息运动中使用视觉效果的具体方式.
研究的目的:
- 分析COVID-19错误信息中使用的视觉图像的框架和功能.
- 识别如何使用视觉图像来说明,证据,或假装在虚假声明中的权威.
- 在错误信息中区分操纵和错误标记的视觉内容.
主要方法:
- 对96个COVID-19视觉图像的例子进行了混合方法分析,这些视觉图像被评为虚假或误导.
- 对视觉内容进行了分析,以了解它们在错误信息中的框架和功能角色.
- 根据操纵技术对示例进行了分类,将简单的改变与先进的AI方法区分开来.
主要成果:
- 在错误信息中,我们发现了六个不同的和视觉效果的三个主要功能.
- 超过一半的分析视觉效果作为明确证据虚假的说法,主要是通过错误标签.
- 发现了少数被操纵的视觉效果,所有这些都是使用基本工具创建的,没有人工智能生成的深度假的实例.
结论:
- 视觉在COVID-19错误信息中发挥着多方面的作用,超越了简单的表现.
- 错误标记的视觉图像的普遍性强调了来源验证和上下文分析的重要性.
- 未来的研究应该考虑视觉功能和分析技术的更广泛范围,而不仅仅是代表性方面.
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