Click the star to add/remove an item to/from your individual schedule.
You need to be logged in to avail of this functionality.

Accepted Paper:

(Big) data brokers, identity graphs and social sorting  
Stefan Strauß (Austrian Academy of Sciences)

Paper short abstract:

This contribution discusses practices of data brokers focussing on the production of identity graphs as core feature thereof. Automated mapping of individuals' identities serves various (indistinct) purposes including profiling, scoring, and social sorting with accordingly serious societal impacts.

Paper long abstract:

Embedded in the big data paradigm is the questionable proposition of data being the "new oil of the digital economy" (Wired 2014). Accordingly, data brokerage flourishes, based on the exploitation of information from various sources. Large-scale data gathering practices also comprise information about individuals, including their online and offline behaviour and actions. Behind the scenes, these practices involve various actors, perceivable as "surveillant assemblage" (Haggerty/Ericson 2000). Companies like Acxiom, LexisNexis, Oracle or Palantir Technologies gather and monetize massive amounts of consumer information for data-driven marketing and many other purposes. Palantir, e.g., is among the strategic partners of the NSA; involved in the creation of the surveillance tool "XKeyscore" as revealed by Edward Snowden (Greenwald 2014; Biddle 2017). Among other things, this tool categorises users of privacy-friendly software as "extremists" (Doctrow 2014). Also Oracle cooperates with the NSA. There is thus a close relationship between big data and surveillance (Lyon 2014) where economic practices and modalities of security governance increasingly overlap. Social structures are exposed to this indistinct interplay and incrementally alter through semi-automated practices of (big) data processing (Strauß 2018). This contribution discusses these practices with a focus on a crucial mechanism thereof: the production of identity graphs "including what people say, what they do and what they buy" (Oracle 2015). Basically, these practices exploit our "identity shadows" (Strauß 2011) whereas individuals are profiled in online and offline environments to produce accurate models of their identities, serving various purposes and business cases in private and public sectors.

Panel G03
Technologies that count: big data and social order
  Session 1