本研究展示了利用谷歌云视觉自动图像标注技术创建并分析英国肥胖症小型新闻多模态语料库的过程，以探讨图像标注分析的潜在价值。笔者利用 Wordsmith 工具分析不同报刊对肥胖症话语的构建： 首先比较各报纸的关键词，其次分析每份报纸中的图像关键标注及其搭配词，最后结合文本和图像标注进行图文关系综合分析。三种分析相互补充，使结论更全面，证实了使用谷歌云视觉工具创建和分析多模态语料库的价值。本文最后探讨了该方法的潜在优势，有助于深化人们对图像标注的认识，为语料库辅助的多模态话语研究领域开辟新思路。

This study describes the creation and analysis of a small multimodal corpus of British news articles about obesity, where tags were assigned to images in the articles using the automatic tagger Google Cloud Vision. In order to illustrate the potential for analysis of image tags, the corpus analysis tool WordSmith was used to identify differences between newspapers in the ways that obesity was framed. Three forms of analysis were carried out—the first simply compared keywords across the newspapers, the second examined key visual tags and their collocates associated with each newspaper, while the third incorporated a combined analysis of words and image tags. The three analyses produced complementary findings, indicating the value in using Google Cloud Vision in creating and analysing multimodal corpora. The paper ends by reflecting on the method undertaken, while considering how additional research could improve our understanding of image tagging.