The phenomenon of banner blindness explains that users can mentally ignore online advertisements (ads). However, eye-tracking studies have shown that users still fixate on ads, and even without direct gaze, ads still fall within a user's peripheral vision, which may negatively overload cognition. It is therefore unknown how blind, banner blindness, truly is, and what other effect ads may have on user's information seeking. To address this gap, a within-subjects design experiment was conducted with 37 participants who performed search tasks from the TREC 2017 Common Core News Collection, where 3 search tasks contained various types of ads, and one search task had no ads. Although our results showed that on average, participants retrieved similar amounts of relevant documents regardless of whether ads were present or absent, participants took significantly longer achieving this performance when ads were present. Furthermore, when ads were absent, participants reported less frustration, and not only believed they learned more, but a post-task recall test showed that participants actually did learn up to 38% more. Consequently, our findings suggest that banner blindness is more costly than just mere annoyance, and that the influence of ads on user's information retrieval recall may extend current theories of visual crowding.

Perceptual Speed (PS) is a cognitive ability defined by an individual's accuracy and speed to scan information while completing visual search tasks. Prior studies using PS tests have demonstrated that PS affects multiple factors in Information Retrieval (IR), such as a user's search performance, interaction with the system, time spent completing tasks, and subjective impression of their workload. With greater knowledge of PS, systems could be designed that accommodate users with low PS to improve their overall search experience. However, in this perspectives paper, we analyse how PS tests have been used in IR, and identify multiple uncertainties regarding PS content, administration, analysis, and reporting of findings. Consequently, we aim to stir discussion between IR researchers by drawing awareness to these issues. As a result, we further discuss challenges involved in advancing how future PS tests are used in IR. Finally, we propose recommendations that have the potential for enhancing the reliability and validity of current PS tests.

Perceptual Speed (PS) is a cognitive ability that is known to affect multiple factors in Information Retrieval (IR) such as a user's search performance and subjective experience. However PS tests are difficult to administer which limits the design of user-adaptive systems that can automatically infer PS to appropriately accommodate low PS users. Consequently, this paper evaluated whether PS can be automatically classified from search behaviour using several machine learning models trained on features extracted from TREC Common Core search task logs. Our results are encouraging: given a user's interactions from one query, a Decision Tree was able to predict a user's PS as low or high with 86% accuracy. Additionally, we identified different behavioural components for specific PS tests, implying that each PS test measures different aspects of a person's cognitive ability. These findings motivate further work for how best to design search systems that can adapt to individual differences.