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Declared but Unaccountable: Measuring the Seller-Identity Gap in Advertising Supply-Chain Transparency
arXiv cs.NI0 views
arXiv:2610.14661v2 Announce Type: replace-cross Abstract: Public advertising transparency relies on a minimum accountability condition: an account authorized by a publisher in ads$.$txt or app-ads$.$txt should appear in the applicable sellers$.$json registry. When an available registry omits the declared seller ID, the authorization remains visible and machine-readable, but its public verification path breaks. We call this failure the seller-identity gap. We measure the gap using 233.4 million normalized advertising-transparency records and an absent-only, coverage-aware evidence rule. A declaration enters the numerator only when the applicable registry is available and omits its seller ID; unavailable, malformed, confidential, and other non-evaluable states remain separate. The resulting row-level floor is 24.25% in a high-popularity, low-removal reference population and 30.71% among publishers associated with at least 100 copyright-removal requests, a 6.45 percentage-point increase. The gap then remains near one third at stricter cumulative thresholds. Standardizing the populations to common weights over 1,469 shared ad systems reduces the primary contrast to 4.65 points: about 72% remains within systems, while 28% forms a composition-associated residual. We connect these population estimates to recurring seller-account coordinates, byte-identical declaration configurations, and provenance-bearing case packets. We frame this declaration-centered investigative use of public advertising records as Ad Transparency Intelligence: it reconstructs declared supply-chain relationships, identifies where public verification stops, and prioritizes evidence for corroboration without equating correlation with attribution. Advertising transparency supports accountability and investigation only when visible authorizations remain publicly verifiable.
Source:https://arxiv.org/abs/2610.14661PreviousArcal\'{i}s: Accelerating Remote Procedure Calls Using a L\'{i}ghtweight Near-Cache SolutionNextAmora: Communication-Efficient Private Approximate Nearest Neighbors Search
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