@inproceedings{visokay-etal-2026-social,
    title = "Social Construction of Urban Space: Using {LLM}s to Identify Neighborhood Boundaries From {C}raigslist Ads",
    author = "Visokay, Adam  and
      Bagley, Ruth  and
      Hess, Chris  and
      Kennedy, Ian  and
      Crowder, Kyle  and
      Voigt, Rob  and
      Peskoff, Denis",
    editor = "Card, Dallas  and
      Field, Anjalie  and
      Keith, Katherine  and
      Mendelsohn, Julia",
    booktitle = "Proceedings of the Seventh Workshop on Natural Language Processing and Computational Social Science",
    month = jul,
    year = "2026",
    address = "San Diego",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.nlpcss-1.18/",
    pages = "307--321",
    ISBN = "979-8-89176-426-2",
    abstract = "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."
}