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All the Homes: Zillow and the Operational Context of Data

  • Yanni LoukissasEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10766)

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 operationalizes data 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.

Keywords

Data Context Housing 

References

  1. 1.
    Kitchin, R., Lauriault, T.P.: Towards critical data studies: charting and unpacking data assemblages and their work. Social Science Research Network, Rochester (2014)Google Scholar
  2. 2.
    Small, B.: FTC report examines data brokers. Federal Trade Commission (2014)Google Scholar
  3. 3.
    Yelp Homepage. https://www.yelp.com. Accessed 15 Dec 2017
  4. 4.
    Nextdoor Homepage. https://nextdoor.com. Accessed 15 Dec 2017
  5. 5.
    Uber Homepage. https://uber.com. Accessed 15 Dec 2017
  6. 6.
    Zillow Homepage. https://www.zillow.com. Accessed 15 Dec 2017
  7. 7.
    Seaver, N.: The nice thing about context is that everyone has it. Media Cult. Soc. 37(7), 1101–1109 (2015)CrossRefGoogle Scholar
  8. 8.
    Dourish, P.: What we talk about when we talk about context. Pers. Ubiquit. Comput. 8(1), 11–30 (2004)CrossRefGoogle Scholar
  9. 9.
    Geertz, C.: The Interpretation of Cultures: Selected Essays. Basic Books, New York (1973)Google Scholar
  10. 10.
    Federal Trade Commission: Data Brokers: A Call for Transparency and Accountability. Government of the United States (2014)Google Scholar
  11. 11.
    Crampton, J.W.: Mapping: A Critical Introduction to Cartography and GIS. Wiley, Hoboken (2011)Google Scholar
  12. 12.
    Pearson, D.: Location, location, location. The New York Times (2009). http://www.nytimes.com/2009/06/28/magazine/28FOB-onlanguage-t.html. Accessed 13 Nov 2017
  13. 13.
    Robinson, A.H.: The Look of Maps. University of Wisconsin Press, Madison (1952)Google Scholar
  14. 14.
    Baudrillard, J.: Simulations and Simulacra. Sheila Glaser (trans). University of Michigan Press, Ann Arbor (1984)Google Scholar
  15. 15.
    Kitchin, R., Gleeson, J., Dodge, M.: Unfolding mapping practices: a new epistemology for cartography. Trans. Inst. Br. Geogr. 3(3), 480–496 (2013)CrossRefGoogle Scholar
  16. 16.
    From an interview by the author (2016)Google Scholar
  17. 17.
    Rascoff, S., Humphries, S.: Zillow Talk: Rewriting the Rules of Real Estate. Grand Central Publishing, New York (2015)Google Scholar
  18. 18.
    Murray, J.: Hamlet on the Holodeck. MIT Press, Cambridge (1998)Google Scholar
  19. 19.
    Bogost, I.: Persuasive Games: The Expressive Power of Videogames. MIT Press, Cambridge (2007)Google Scholar
  20. 20.
    Seaver, N.: Algorithms as culture: some tactics for the ethnography of algorithmic systems. Big Data Soc. 4(2) (2017)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Georgia Institute of TechnologyAtlantaUSA

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