两个真相和一个谎言：使用Amazon Alexa探索COVID-19错误信息的软调节
Two Truths and a Lie: Exploring Soft Moderation of COVID-19 Misinformation with Amazon Alexa
摘要：
在本文中，我们分析了第三方亚马逊Alexa技能回复COVID-19疫苗推文时的感知准确性。我们模仿了Twitter对COVID-19错误信息内容的软审核，包括警告封面和警告标签，以调查第三方技能是否会影响用户如何以及何时注意这些警告。来自304名参与者的研究结果表明，即使从文本转换为语音，语音背面警告封面也可能无法按预期工作。我们控制了COVID-19疫苗接种犹豫和政治倾向，发现疫苗接种犹豫的Alexa用户忽略了任何类型的警告，只要推文与他们的个人信仰一致。政治上独立的用户对Alexa的信任度低于政治上的用户，这有助于他们准确地感知真实的COVID-19信息。我们讨论了语音助理的软调节适应，以达到遏制COVID-19错误信息的预期效果。
英文摘要：
In this paper, we analyzed the perceived accuracy of COVID-19 vaccine Tweets when they were spoken back by a third-party Amazon Alexa skill. We mimicked the soft moderation that Twitter applies to COVID-19 misinformation content in both forms of warning covers and warning tags to investigate whether the third-party skill could affect how and when users heed these warnings. The results from a 304-participant study suggest that the spoken back warning covers may not work as intended, even when converted from text to speech. We controlled for COVID-19 vaccination hesitancy and political leanings and found that the vaccination hesitant Alexa users ignored any type of warning as long as the Tweets align with their personal beliefs. The politically independent users trusted Alexa less then their politically-laden counterparts and that helped them accurately perceiving truthful COVID-19 information. We discuss soft moderation adaptations for voice assistants to achieve the intended effect of curbing COVID-19 misinformation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
