Tilted platforms: rental housing technology and the rise of urban big data oligopolies.

ABSTRACT: This article interprets emerging scholarship on rental housing platforms-particularly the most well-known and used short- and long-term rental housing platforms-and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators' own financial and political interests. The question of which data-and people-are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations. POLICY AND PRACTICE RECOMMENDATIONS: As rental housing technologies upend traditional market processes in favor of platform oligopolies, policymakers must reorient these processes toward the public good.Long-term and short-term rental platforms offer different market benefits and drawbacks, but the latter in particular requires proactive regulation to mitigate harm.At a minimum, policymakers must require that short-term rental platforms provide the information necessary for cities to enforce current, let alone new, housing regulations.Practitioners should be cautious inferring market conditions from rental housing platform data, due to difficult-to-measure sampling biases.

The Unequal Availability of Rental Housing Information Across Neighborhoods.

As more urban residents find their housing through online search tools, recent research has theorized the potential for online information to transform and equalize the housing search process. Yet, very little is known about what rental housing information is available online. Using a corpus of millions of geocoded Craigslist advertisements for rental housing across the 50 largest metropolitan statistical areas in the United States merged with census tract-level data from the American Community Survey, we identify and describe the types of information commonly included in listings across different types of neighborhoods. We find that in the online housing market, renters are exposed to fundamentally different types of information depending on the ethnoracial and socioeconomic makeup of the neighborhoods where they are searching.

The COVID-19 Pandemic and the Rental Market: Evidence From Craigslist.

Past research has demonstrated the racially and spatially uneven impacts of economic shocks and environmental disasters on various markets. In this article, we examine if and how the first few months of the COVID-19 pandemic affected the market for rental housing in the 49 largest metropolitan areas in the United States. Using a unique data set of new rental listings gathered from Craigslist and localized measures of the pandemic's severity we find that, from mid-March to early June, local spread of COVID-19 is followed by reduced median and mean rent. However, this trend is driven by dropping rents for listings in Black, Latino, and diverse neighborhoods. Listings in majority White neighborhoods experience rent increases during this time. Our analyses make multiple contributions. First, we add to the burgeoning literature examining the rental market as a key site of perpetuating sociospatial inequality. Second, we demonstrate the utility of data gathered online for analyzing housing. And third, by reflecting on research that shows how past crises have increased sociospatial inequality and up-to-date work showing the racially and spatially unequal effects of the COVID-19 pandemic, we discuss some possible mechanisms by which the pandemic may be affecting the market for rental housing as well as implications for long-term trends.

Effect of neighborhood stigma on economic transactions.

The hypothesis of neighborhood stigma predicts that individuals who reside in areas known for high crime, poverty, disorder, and/or racial isolation embody the negative characteristics attributed to their communities and experience suspicion and mistrust in their interactions with strangers. This article provides an experimental test of whether neighborhood stigma affects individuals in one domain of social life: economic transactions. To evaluate the neighborhood stigma hypothesis, this study adopts an audit design in a locally organized, online classified market, using advertisements for used iPhones and randomly manipulating the neighborhood of the seller. The primary outcome under study is the number of responses generated by sellers from disadvantaged relative to advantaged neighborhoods. Advertisements from disadvantaged neighborhoods received significantly fewer responses than advertisements from advantaged neighborhoods. Results provide robust evidence that individuals from disadvantaged neighborhoods bear a stigma that influences their prospects in economic exchanges. The stigma is greater for advertisements originating from disadvantaged neighborhoods where the majority of residents are black. This evidence reveals that residence in a disadvantaged neighborhood not only affects individuals through mechanisms involving economic resources, institutional quality, and social networks but also affects residents through the perceptions of others.

Elicitation of specific syntactic structures in primary progressive aphasia.

Many patients with primary progressive aphasia (PPA) are impaired in syntactic production. Because most previous studies of expressive syntax in PPA have relied on quantitative analysis of connected speech samples, which is a relatively unconstrained task, it is not well understood which specific syntactic structures are most challenging for these patients. We used an elicited syntactic production task to identify which syntactic structures pose difficulties for 31 patients with three variants of PPA: non-fluent/agrammatic, semantic and logopenic. Neurodegenerative and healthy age-matched participants were included as controls. As expected, non-fluent/agrammatic patients made the most syntactic errors. The structures that resulted in the most errors were constructions involving third person singular present agreement, and constructions involving embedded clauses. Deficits on this elicited production task were associated with atrophy of the left posterior inferior frontal gyrus.

Connected speech production in three variants of primary progressive aphasia.

Primary progressive aphasia is a clinical syndrome defined by progressive deficits isolated to speech and/or language, and can be classified into non-fluent, semantic and logopenic variants based on motor speech, linguistic and cognitive features. The connected speech of patients with primary progressive aphasia has often been dichotomized simply as 'fluent' or 'non-fluent', however fluency is a multidimensional construct that encompasses features such as speech rate, phrase length, articulatory agility and syntactic structure, which are not always impacted in parallel. In this study, our first objective was to improve the characterization of connected speech production in each variant of primary progressive aphasia, by quantifying speech output along a number of motor speech and linguistic dimensions simultaneously. Secondly, we aimed to determine the neuroanatomical correlates of changes along these different dimensions. We recorded, transcribed and analysed speech samples for 50 patients with primary progressive aphasia, along with neurodegenerative and normal control groups. Patients were scanned with magnetic resonance imaging, and voxel-based morphometry was used to identify regions where atrophy correlated significantly with motor speech and linguistic features. Speech samples in patients with the non-fluent variant were characterized by slow rate, distortions, syntactic errors and reduced complexity. In contrast, patients with the semantic variant exhibited normal rate and very few speech or syntactic errors, but showed increased proportions of closed class words, pronouns and verbs, and higher frequency nouns, reflecting lexical retrieval deficits. In patients with the logopenic variant, speech rate (a common proxy for fluency) was intermediate between the other two variants, but distortions and syntactic errors were less common than in the non-fluent variant, while lexical access was less impaired than in the semantic variant. Reduced speech rate was linked with atrophy to a wide range of both anterior and posterior language regions, but specific deficits had more circumscribed anatomical correlates. Frontal regions were associated with motor speech and syntactic processes, anterior and inferior temporal regions with lexical retrieval, and posterior temporal regions with phonological errors and several other types of disruptions to fluency. These findings demonstrate that a multidimensional quantification of connected speech production is necessary to characterize the differences between the speech patterns of each primary progressive aphasic variant adequately, and to reveal associations between particular aspects of connected speech and specific components of the neural network for speech production.