Can Ad-supported Online Publishing Survive Privacy Regulations and Ad-Blockers?
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Date: 04 JUNE 2025 from 17:30 to 19:00
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Event location: Aula III via Francesco Selmi 2 - Bologna, Piano Terra.
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Type: Lectures
Speaker
ISA Visiting Fellow - Cristian Borcea
Professor Department of Computer Science and Engeneering, USA
ATTENDANCE
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in presence - book your seat
Book your seat within June 4, 12 p.m. The places will be assigned on “first come first served” basis.
The accessibility of the building is barrier-free, with pathway from the side entrance with building slide to the classroom located on the ground floor. Also available to persons with disabilities is a single-seat anthropometric bench with variable elevation and tilt positioned near the desk.
Since our society receives most of its information online, a high-quality online press plays a crucial role in democracy, especially in light of the mounting volumes of fake news and disinformation. Most of us got used to reading online press for free, and this is made possible by online advertisement revenue. However, in the recent years two separate trends have started to endanger this publishing model: the regulations introduced by government across the world, such as GDPR in Europe, to protect the user privacy, and the ad-blocker tools installed in the browsers to remove the annoyance caused by ads. Both trends result in significant revenue loss for publishers and may lead to pay walls, under which users need to pay to read high-quality content, or even the disappearance of local or niche publishers. The main question that we address in this lecture is how to balance ad revenue, user privacy, and user experience on ad-supported publishing websites. To address this question, we collaborated with major international publishers in the past ten years for a comprehensive study of ad-supported online publishing. The lecture will cover our findings and solutions in terms of GDPR [non-]compliance and the need for better privacy regulations, distributed machine learning techniques that allow targeted advertisement while protecting user privacy, and personalized dynamic counter ad-blocking using deep learning to avoid negative effects of forcing users to disable ad-blockers.