Rental listings offer a window into how urban space is socially constructed through language. We analyze Chicago Craigslist rental advertisements from 2018 to 2024 to examine how listing agents characterize neighborhoods, identifying mismatches between institutional boundaries and neighborhood claims. Through manual and large language model annotation, we classify unstructured listings from Craigslist according to their neighborhood. Further geospatial analysis reveals three distinct patterns: properties with conflicting neighborhood designations due to competing spatial definitions, border properties with valid claims to adjacent neighborhoods, and "reputation laundering" where listings claim association with distant, desirable neighborhoods. Through topic modeling, we identify patterns that correlate with spatial positioning: listings further from neighborhood centers emphasize different amenities than centrally-located units. Natural language processing techniques reveal how definitions of urban spaces are contested in ways that traditional methods overlook.

翻译：租赁列表为理解语言如何社会建构城市空间提供了一个窗口。我们分析了2018年至2024年芝加哥克雷格列表的租赁广告，以考察列表发布者如何描述邻里特征，识别制度性边界与邻里主张之间的错位。通过人工与大语言模型标注，我们将克雷格列表中的非结构化房源信息按所属邻里进行分类。进一步的地理空间分析揭示了三种典型模式：因空间定义竞争而产生邻里归属冲突的房产、对相邻邻里具有合理主张的边界房产，以及通过声称与遥远且理想的邻里存在关联以进行"声誉洗白"的列表。通过主题建模，我们发现与空间位置相关的描述模式：远离邻里中心的房源所强调的便利设施与中心区域单元存在差异。自然语言处理技术揭示了传统方法所忽视的城市空间定义如何在语言层面被争夺与协商。