In a rapidly globalizing and digital world, content such as book and product reviews created by people from diverse cultures are read and consumed by others from different corners of the world. In this paper, we investigate the extent and patterns of gaps in understandability of book reviews due to the presence of culturally-specific items and elements that might be alien to users from another culture. Our user-study on 57 book reviews from Goodreads reveal that 83\% of the reviews had at least one culture-specific difficult-to-understand element. We also evaluate the efficacy of GPT-4o in identifying such items, given the cultural background of the reader; the results are mixed, implying a significant scope for improvement. Our datasets are available here: https://github.com/sougata-ub/reading_between_lines

翻译：在一个快速全球化与数字化的世界中，由来自不同文化背景的人们创作的书籍和产品评论等内容，正被世界各地的其他用户阅读和消费。本文研究了由于存在特定文化元素和项目（这些元素对于来自另一文化的用户而言可能较为陌生）而导致的书籍评论可理解性鸿沟的程度与模式。我们对来自Goodreads的57篇书评进行的用户研究表明，83%的评论至少包含一个文化特定且难以理解的元素。我们还评估了GPT-4o在给定读者文化背景的情况下识别此类项目的效能；结果喜忧参半，意味着存在巨大的改进空间。我们的数据集可在此处获取：https://github.com/sougata-ub/reading_between_lines