Dr. Nikolaous Laoutaris talks about the landscape and methods of online advertising targeting to create personalized ads based on the user’s behavior.
In this talk Dr. Laoutaris will present his recent results on detecting behavioural targeting in online advertising. He will describe the methods developed to: 1) audit web domains for behavioural targeting by training artificial “personas”, collecting ads, and identifying correlations between training and landing pages; 2) audit individual impression by using only browser history and online taxonomies for web-pages; 3) audit individual impression by using crowdsourced data from multiple users.
He will also present initial findings on the amount of targeting going on, the most targeted categories, the existence of targeting even in sensitive personal categories for which the law requires explicit user consent, as well as results on identifying the chain of companies involved in the delivery of such ads.
Going beyond online advertising, Dr. Laoutaris will also present earlier work on detecting online price discrimination as well as his community building efforts in setting up and growing the Data Transparency Lab (https://datatransparencylab.org/).
Registration open from October 23rd. Contact: firstname.lastname@example.org