谷歌反向图片搜索在辟谣中效果有限，反而常推送错误信息。
From Verification to Amplification: Auditing Reverse Image Search as Algorithmic Gatekeeping in Visual Misinformation Fact-checking
- 通过反向搜图分析15天内新出现的误导性图像
- 搜索结果中辟谣内容不足30%，且被重复错误信息淹没
- 越早搜索结果质量越差，存在数据空白期
随着视觉虚假信息日益泛滥，平台算法作为用户验证信息的中介，其作用愈发关键。然而，反向图片搜索（RIS）等算法把关工具如何影响用户在辟谣过程中的信息接触仍不明确。本研究系统审计了谷歌RIS，在15天窗口期内对新识别的误导性图像进行反向搜索，并分析了34,486条排名靠前的结果。发现谷歌RIS返回大量无关信息和重复错误信息，而辟谣内容占比不足30%。辟谣内容在排名中面临可见性挑战，被错误信息和无关内容掩盖。研究还揭示了搜索结果质量随时间呈倒U型变化，可能源于视觉假象刚出现时搜索引擎的“数据空洞”。这些发现拓展了视觉虚假信息验证研究，将算法把关研究延伸至视觉领域。
原文摘要 · Abstract (English)
As visual misinformation becomes increasingly prevalent, platform algorithms act as intermediaries that curate information for users' verification practices. Yet, it remains unclear how algorithmic gatekeeping tools, such as reverse image search (RIS), shape users' information exposure during fact-checking. This study systematically audits Google RIS by reversely searching newly identified misleading images over a 15-day window and analyzing 34,486 collected top-ranked search results. We find that Google RIS returns a substantial volume of irrelevant information and repeated misinformation, whereas debunking content constitutes less than 30% of search results. Debunking content faces visibility challenges in rankings amid repeated misinformation and irrelevant information. Our findings also indicate an inverted U-shaped curve of RIS results page quality over time, likely due to search engine "data voids" when visual falsehoods first appear. These findings contribute to scholarship of visual misinformation verification, and extend algorithmic gatekeeping research to the visual domain.
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