论文标题
有意义的上下文，危险信号还是两者兼而有之？用户在Twitter上的增强错误信息警告的偏好
Meaningful Context, a Red Flag, or Both? Users' Preferences for Enhanced Misinformation Warnings on Twitter
论文作者
论文摘要
警告用户有关社交媒体上的错误信息并不是一个简单的可用性任务。软节制必须在揭露虚假性和避免节制偏见的同时保持社交媒体消费流程之间的平衡。因此，平台在可疑的错误信息内容下使用通用文本采用了可区分的警告标签。这种方法导致了一个不利的结果，在警告“适得其反”的情况下，用户相信错误的信息而不是更少。作为回应，我们开发了对错误信息警告的增强能力，在该警告中，在信息危害的背景下建议用户，并暴露于标准警告图标。我们在337个参与者可用性研究中使用Twitter的原始警告标签进行了A/B评估。大多数参与者更喜欢增强能力，将其推向识别和避免错误信息。加强的警告标签受到政治左倾的最爱，在较小程度上是温和的参与者，但他们也吸引了大约三分之一的右倾参与者。教育水平是塑造参与者偏好的唯一人口因素。我们利用我们的发现来提出用户限制的改进，以在社交媒体上的误解中柔和地适度进行改进。
Warning users about misinformation on social media is not a simple usability task. Soft moderation has to balance between debunking falsehoods and avoiding moderation bias while preserving the social media consumption flow. Platforms thus employ minimally distinguishable warning tags with generic text under a suspected misinformation content. This approach resulted in an unfavorable outcome where the warnings "backfired" and users believed the misinformation more, not less. In response, we developed enhancements to the misinformation warnings where users are advised on the context of the information hazard and exposed to standard warning iconography. We ran an A/B evaluation with the Twitter's original warning tags in a 337 participant usability study. The majority of the participants preferred the enhancements as a nudge toward recognizing and avoiding misinformation. The enhanced warning tags were most favored by the politically left-leaning and to a lesser degree moderate participants, but they also appealed to roughly a third of the right-leaning participants. The education level was the only demographic factor shaping participants' preferences. We use our findings to propose user-tailored improvements in the soft moderation of misinformation on social media.
