Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://dx.doi.org/10.48550/ar...
Article . 2024
License: CC BY
Data sources: Datacite
DBLP
Preprint . 2024
Data sources: DBLP
versions View all 4 versions
addClaim

Consumer Manipulation via Online Behavioral Advertising

Authors: Lex Zard;

Consumer Manipulation via Online Behavioral Advertising

Abstract

Online behavioral advertising (OBA) has a significant role in the digital economy. It allows advertisers to target consumers categorized according to their algorithmically inferred interests based on their behavioral data. As Alphabet and Meta gatekeep the Internet with their digital platforms and channel most of the consumer attention online, they are best placed to execute OBA and earn profits far exceeding fair estimations. There are increasing concerns that gatekeepers achieve such profitability at the expense of consumers, advertisers, and publishers who are dependent on their services to access the Internet. In particular, some claim that OBA systematically exploits consumers' decision-making vulnerabilities, creating internet infrastructure and relevant markets that optimize for consumer manipulation. Intuitively, consumer manipulation via OBA comes in tension with the ideal of consumer autonomy in liberal democracies. Nevertheless, academia has largely overlooked this phenomenon and instead has primarily focused on privacy and discrimination concerns of OBA. This article redirects academic discourse and regulatory focus on consumer manipulation via OBA. In doing so, first, this article elaborates on how OBA works. Second, it constructs an analytic framework for understanding manipulation. Third, it applies the theory of manipulation to OBA. As a result, this article illustrates the extent to which OBA leads to consumer manipulation. Crucially, this article is purely analytic and avoids normative evaluation of consumer manipulation via OBA. Evaluating consumer manipulation harms of OBA is an equally important but separate task and is pursued in another publication.

Keywords

FOS: Computer and information sciences, Computer Science - Computers and Society, Computers and Society (cs.CY)

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green