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Street-level

Google Street View’s abstraction by datafication

Bibliographic Data

ID12656706
AuthorsAaron Shapiro (0000-0003-4501-6914, University of Pennsylvania, corresponding author)
Year2017
Volume20
Issue3
Pages1201-1219
Publication date2017-01-16
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueNew Media & Society (JOURNAL)
Journal identifiersISSN: 1461-4448 • E-ISSN: 1461-7315
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/1461444816687293
OpenAlexW2578619259
LanguageEN
Citations received19
References cited54

While aerial photography is associated with vertical objectivity and spatial abstractions, street-level imagery appears less political in its orientation to the particularities of place. I contest this assumption, showing how the aggregation of street-level imagery into “big datasets” allows for the algorithmic sorting of places by their street-level visual qualities. This occurs through an abstraction by “datafication,” inscribing new power geometries onto urban places through algorithmic linkages between visual environmental qualities, geographic information, and valuations of social worth and risk. Though largely missing from media studies of Google Street View, similar issues have been raised in critiques of criminological theories that use place as a proxy for risk. Comparing the Broken Windows theory of criminogenesis with big data applications of street-level imagery informs a critical media studies approach to Google Street View. The final section of this article suggests alternative theoretical orientations for algorithm design that avoid the pitfalls of essentialist equations of place with social character

Abstraction · Aesthetics · Art · Big data · CONTEST · Data mining · Data science · Epistemology · Essentialism · Objectivity (philosophy · Political science · Politics · Social media · Sociology · World Wide Web · Computer Science · Crime Patterns and Interventions · Law · Law in Society and Culture · Wildlife Conservation and Criminology Analyses

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Unique citing works19
Citations per year2,11
Citation span2017 - 2025 (9)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 18

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