Abstract: Analysis of an Internet content publisher's web pages to identify third-party vendor tags, as well as piggyback vendor tags called during execution of a given web page, that ultimately cause various types of secondary (“foreign”) content (e.g., ads, trackers, analytics, widgets, privacy assets) to be present in the content publisher's web pages when rendered by a browser on a client computing device. Such analysis also reveals the sources of the tags and the foreign content, and parent-child relationships (“parentage”) amongst vendor tags. A graphical representation is then rendered that includes one or more visualizations of the identified vendor tags, and the corresponding sources of the tags and the foreign content in the content publisher's web pages, as well as other information relating to the tags, the foreign content and their sources (e.g., parentage, classification of content, timing of called tags, latency resulting from tags, secure/unsecure calls to foreign resources, etc.).
Type:
Application
Filed:
March 2, 2016
Publication date:
December 15, 2016
Applicant:
GHOSTERY, INC.
Inventors:
Patrick M. Nielsen, Vern DeMille, Joseph C. Kilrain, Scott Meyer, Justin Donohoo, Edward Kozek, Bree Van Oss, Jose Maria Signanini
Abstract: A computerized system and techniques facilitate the monitoring and management of online behaviorally-targeted advertising. In certain embodiments, electronic notifications related to advertising practices of members of an online advertising ecosystem are presented to users based on the discovery of elements of online content aimed at delivering targeted advertising messages to viewers of the content.
Type:
Grant
Filed:
December 17, 2010
Date of Patent:
June 7, 2016
Assignee:
Ghostery, Inc.
Inventors:
Scott B. Meyer, Felix Shnir, Simeon Simeonov, Edward Kozek, Colin O'Malley, Daniel Jaye
Abstract: A system for accurately estimating global impression volumes at tag and host levels, and for computing global page views and reach estimates, collects impression volumes for various tracking technologies and for several hosts from a panel of users. The collected panel data is normalized, e.g., to minimize spurious and/or non-human activity data. A scaling factor is computed using measured global impression volume of a reference tag and impression volume of the reference tag with respect to the panel. The required global estimates are obtained by scaling the normalized panel data using the computed scaling factor.