Scholarlink

<p>In this paper, we build on the theory of ecologically rational heuristics to demonstrate the effect of erroneously placed warning labels on news headlines. Through three between-subjects experiments (n = 1313), we show that people rely on warning labels when choosing to trust news, <i>even when those labels are wrong.</i> We argue that this over-reliance on content labels is due to ecological rationality adaptations to current media environments, where warning labels are human-generated and mostly correct. Specifically, news consumers form heuristics based on past interactions with warning labels, and those heuristics can spill-over into new media environments where warning label errors are more frequent. The most important implication of these results is that it is more important to thoughtfully consider what information needs to be labeled than it is to attempt to label all false information. We discuss how this implication impacts our ability to scale warning label systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

People adhere to content warning labels even when they are wrong due to ecologically rational adaptations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月22日

查看全文
  • Benjamin D. Horne,
  • Dorit Nevo

摘要

In this paper, we build on the theory of ecologically rational heuristics to demonstrate the effect of erroneously placed warning labels on news headlines. Through three between-subjects experiments (n = 1313), we show that people rely on warning labels when choosing to trust news, even when those labels are wrong. We argue that this over-reliance on content labels is due to ecological rationality adaptations to current media environments, where warning labels are human-generated and mostly correct. Specifically, news consumers form heuristics based on past interactions with warning labels, and those heuristics can spill-over into new media environments where warning label errors are more frequent. The most important implication of these results is that it is more important to thoughtfully consider what information needs to be labeled than it is to attempt to label all false information. We discuss how this implication impacts our ability to scale warning label systems.