My article “Home Sharing as Affordable Housing for All? Revealing the Exclusionary Language of Shared Rental Listings through AI,” co-authored with Julia Harten and Madison Lore, has just been published in Environment and Planning A: Economy and Space. You can download it open-access from EP-A.

In expensive, exclusive cities, shared housing is often a pragmatic answer to the affordability crisis: rent a room to split costs and access neighborhoods that would otherwise be out of reach. Studying ~90,000 Craigslist rental listings in Los Angeles, we show that shared rentals are indeed cheaper and more geographically widespread than small whole-unit apartment rentals. But access to them depends on more than income or availability - it also depends on whether existing tenants imagine you as the “right” kind of person to live with.

Our central finding is that shared housing often turns existing tenants into gatekeepers. Unlike conventional whole-unit rental listings, shared housing listings frequently describe desired personal traits, household rules, lifestyles, privacy expectations, and ideas of compatibility. Some of this is understandable: living with strangers involves real social, financial, and emotional risk. But the language of “fit” often becomes a language of similarity, with listers seeking people of similar age, gender, work status, habits, politics, or culture. Even when race, religion, disability, or immigration status are rarely named directly, exclusion still operates through coded signals, insider language, and assumptions about who will “fit.”

The broader implication is important for housing policy. Shared renting may expand affordable options, but it does not automatically expand equitable access to those options. If the cheapest rooms in desirable neighborhoods are filtered through narrow ideas of compatibility, shared housing can reproduce segregation while appearing informal, personal, and benign. We argue that policymakers should take the relational nature of shared renting seriously, designing protections that reduce risk for co-tenants while making shared homes more accessible to a wider range of people.

From the abstract:

Shared renting offers affordability opportunities in unaffordable neighborhoods, but uniquely impels existing and prospective tenants to match on both unit and personal characteristics—creating new opportunities for discrimination and segregation. This study investigates how this matching unfolds. Do existing tenants construct “idealized co-tenants” to signal their selection criteria and signal who is and is not welcome to apply? We analyze online rental listings in Los Angeles, California through a mixed-methods research design, leveraging both quantitative deep learning models of listing language and qualitative content analysis of how listers present selection criteria. We find that, relative to whole unit listings, shared unit listings uniquely emphasize personal characteristics, rental rules, and privacy concerns. Although selection criteria describing behaviors—rather than personal traits—dominate, references to several protected classes appear. Listers often operationalize compatibility as similarity, relying on in-group communication strategies and covert insider signaling. This suggests how shared housing may perpetuate socio-spatial segregation by restricting precious affordability opportunities to narrow subpopulations. Policymakers should craft tenant protections addressing the unique relational nature of shared renting to enable more diverse shared households and counteract trends that reinforce inequitable status quos.

For more, check out our free open-access article at EP-A.