Dataset of user evaluations of prototypicality, aesthetics, usability and trustworthiness of homepages of banking, e-commerce and university websites.

The dataset contains full-page screenshots of homepages of commercial banking (N = 1033), online shopping (N = 1064), and university (N = 1059) websites, as well as the raw and aggregated user ratings of webpage design prototypicality, visual aesthetics, perceived usability and trustworthiness, and user demographic information. Design prototypicality was measured with three items, including typicality, exemplar goodness, and family resemblance, whereas the other design dimensions were measured with a single item each. Amazon Mechanical Turk crowdworkers (N = 3319 rating sessions) provided their demographic data and rated the homepages online. The demographic data have been anonymized, with generated unique participant IDs replacing MTurk crowdworker IDs. The screenshots are identified with generated IDs to provide partial anonymization for the websites, limiting their potential misuse outside design-related or user experience-related academic research. The raw rating data contain all collected ratings, whereas the aggregated data contain the per-webpage, per-dimension ratings derived solely from the ratings of study-compliant crowdworkers. The non-compliance among crowdworkers was detected based on several indicators, including rate-rerate consistency, seen-unseen webpage recognition, free-form feedback analyses, demographic data analyses, and other indicators. Future research could utilize the dataset either in user studies that require full-page webpages as stimuli, e.g., studies on the determinants of first impression, user preference, and user experience, or in computational research on web design, including computational aesthetics, as this type of research requires a large number of user-rated webpages, which this dataset provides.

Investigating Effects of Typographic Variables on Webpage Reading Through Eye Movements.

Webpage reading is ubiquitous in daily life. As Web technologies allow for a large variety of layouts and visual styles, the many formatting options may lead to poor design choices, including low readability. This research capitalizes on the existing readability guidelines for webpage design to outline several visuo-typographic variables and explore their effect on eye movements during webpage reading. Participants included children and adults, and for both groups typical readers and readers with dyslexia were considered. Actual webpages, rather than artificial ones, served as stimuli. This allowed to test multiple typographic variables in combination and in their typical ranges rather than in possibly unrealistic configurations. Several typographic variables displayed a significant effect on eye movements and reading performance. The effect was mostly homogeneous across the four groups, with a few exceptions. Beside supporting the notion that a few empirically-driven adjustments to the texts' visual appearance can facilitate reading across different populations, the results also highlight the challenge of making digital texts accessible to readers with dyslexia. Theoretically, the results highlight the importance of low-level visual factors, corroborating the emphasis of recent psychological models on visual attention and crowding in reading.