Explaining Why Fake Photos are Fake: Does It Work?
Explaining Why Fake Photos are Fake: Does It Work?
复制标题
解释为什么假照片是假的：它有效吗？
DOI：
10.1145/3567558
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发表时间：
2023
影响因子：
--
通讯作者：
Levchenko, Kirill
中科院分区：
文献类型：
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作者：
Ruffin, Margie;Wang, Gang;Levchenko, Kirill
今天的虚假信息运动可能会使用欺骗性的修改照片来促进虚假的叙述。在某些情况下，观众可能不知道这种改变，因此可能更容易接受这种宣传的叙述。在这项工作中，我们考虑是否可以通过向观众解释图像是如何被操纵来减轻这种影响。为了探索这个想法，我们进行了两部分研究。我们首先进行了一项调查（n=113），以检查用户是否确实不善于识别被操纵的图像。我们的结果验证了这一猜想，因为参与者的表现几乎不比随机猜测好（准确率为60%）。然后，我们在第二次调查（n=543）中探索了我们的主要假设。我们选择了互联网上传播的经过处理的图像，这些图像描绘了政治人物和舆论影响者。参与者被分为三组，分别观看原始（未修改）图像、修改后的图像和修改后的图像与解释。每幅图像代表一个案例研究，并独立于其他图像进行评估。我们发现，简单地突出显示和解释的操纵用户并不总是有效的。当它有效时，它确实有助于使用户不太同意操纵背后的预期信息。然而，令人惊讶的是，这种解释也有相反的解释（例如，负面）影响用户对图像中对象的感觉/情绪。基于这些结果，我们讨论了开放式的问题，可以作为在这一领域的未来研究的基础。
Today's disinformation campaigns may use deceptively altered photographs to promote a false narrative. In some cases, viewers may be unaware of the alteration and thus may more readily accept the promoted narrative. In this work, we consider whether this effect can be lessened by explaining to the viewer how an image has been manipulated. To explore this idea, we conduct a two-part study. We started with a survey (n=113) to examine whether users are indeed bad at identifying manipulated images. Our result validated this conjecture as participants performed barely better than random guessing (60% accuracy). Then we explored our main hypothesis in a second survey (n=543). We selected manipulated images circulated on the Internet that pictured political figures and opinion influencers. Participants were divided into three groups to view the original (unaltered) images, the manipulated images, and the manipulated images with explanations, respectively. Each image represents a single case study and is evaluated independently of the others. We find that simply highlighting and explaining the manipulation to users was not always effective. When it was effective, it did help to make users less agreeing with the intended messages behind the manipulation. However, surprisingly, the explanation also had an opposite (e.g.,negative) effect on users' feeling/sentiment toward the subjects in the images. Based on these results, we discuss open-ended questions which could serve as the basis for future research in this area.