Abstract
This publication describes a technology for evaluating and scoring the advertising load presented to users across digital platforms. The system calculates a user-perceived advertising load by aggregating data at a user-session level and applying percentile-based statistical methods to determine a publisher-level score. This approach provides a robust mechanism for identifying digital environments with excessive advertising that degrades the user experience. The technology utilizes both logged event data and automated crawling techniques to construct a comprehensive view of the advertising landscape. Keywords: advertising load, user session, behavioral score, digital inventory, automated crawling, viewability.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
He, Dongjing; Sheng, Shuyang; Zippel, Richard; Chang, Daniel; Dhuper, Sahil; and Fried, Zachary Loebel, "Measurement and Evaluation of User-Perceived Advertising Load Across Digital Platforms", Technical Disclosure Commons, (May 20, 2026)
https://www.tdcommons.org/dpubs_series/10183