All the homes: Zillow and the operational context of data

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Abstract

Zillow, an online real estate marketplace that seeks to make information available about “all the homes” in the United States, tells us that “data want to be free”. But a close analysis reveals that Zillow works to ground data: to put data into an operational context. I use the phrase “operational context” to denote a setting in which data—for real estate: current listings, tax assessments, and other digital property records—are meant to be fully understood. This paper examines the design of operational contexts for data as well as their cultural and political significance, using Zillow as a case. Zillow was founded in 2006, at the height of the housing bubble. Although practices with real estate have been under scrutiny ever since, the treatment of real estate data has not. This paper examines how Zillow operationalizesdata for the housing market through a combination of analytical, discursive, and algorithmic devices. These dimensions of operational context are less about establishing the truth of data than a level of tractability for prospective buyers and sellers. The operational context for data is not derived from a neutral retrospective view (i.e. where the data come from). Rather, it is a matter of connecting data to an existing cultural system, defined by inherited practices, concepts and affordances that support specific use cases. Operational context can enable interpretation and action based on data, but it can also reify the power of a dominant culture.

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APA

Loukissas, Y. (2018). All the homes: Zillow and the operational context of data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10766 LNCS, pp. 272–281). Springer Verlag. https://doi.org/10.1007/978-3-319-78105-1_31

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