Eric Zeng
University of Washington, Seattle, Washington, United States
Online display advertising on websites is widely disliked by users, with many turning to ad blockers to avoid ``bad'' ads. Recent evidence suggests that today’s ads contain potentially problematic content, in addition to well-studied concerns about the privacy and intrusiveness of ads. However, we lack knowledge of which types of ad content users consider problematic and detrimental to their browsing experience. Our work bridges this gap: first, we create a taxonomy of 15 positive and negative user reactions to online advertising from a survey of 60 participants. Second, we characterize classes of online ad content that users dislike or find problematic, using a dataset of 500 ads crawled from popular websites, labeled by 1000 participants using our taxonomy. Among our findings, we report that users consider a substantial amount of ads on the web today to be clickbait, untrustworthy, or distasteful, including ads for software downloads, listicles, and health & supplements.
https://doi.org/10.1145/3411764.3445459
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)