Efficient URL caching for world wide web crawling
WWW '03 Proceedings of the 12th international conference on World Wide Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
A Survey of Web Information Extraction Systems
IEEE Transactions on Knowledge and Data Engineering
Foundations and Trends in Information Retrieval
Challenges in measuring online advertising systems
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Online stochastic packing applied to display ad allocation
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
User browsing behavior-driven web crawling
Proceedings of the 20th ACM international conference on Information and knowledge management
Detecting and defending against third-party tracking on the web
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Betrayed by your ads!: reconstructing user profiles from targeted ads
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
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Over the past decade, advertising has emerged as the primary source of revenue for many web sites and apps. In this paper we report a first-of-its-kind study that seeks to broadly understand the features, mechanisms and dynamics of display advertising on the web - i.e., the Adscape. Our study takes the perspective of users who are the targets of display ads shown on web sites. We develop a scalable crawling capability that enables us to gather the details of display ads including creatives and landing pages. Our crawling strategy is focused on maximizing the number of unique ads harvested. Of critical importance to our study is the recognition that a user's profile (i.e., browser profile and cookies) can have a significant impact on which ads are shown. We deploy our crawler over a variety of websites and profiles and this yields over 175K distinct display ads. We find that while targeting is widely used, there remain many instances in which delivered ads do not depend on user profile; further, ads vary more over user profiles than over websites. We also assess the population of advertisers seen and identify over 3.7K distinct entities from a variety of business segments. Finally, we find that when targeting is used, the specific types of ads delivered generally correspond with the details of user profiles, and also on users' patterns of visit.