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

Aliaksei Miniukovich; Kathrin Figl

doi:10.1016/j.dib.2023.109976

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

Data Brief. 2023 Dec 18:52:109976. doi: 10.1016/j.dib.2023.109976. eCollection 2024 Feb.

Authors

Aliaksei Miniukovich^{1

2}, Kathrin Figl¹

Affiliations

¹ Department of Information Systems Production and Logistics Management, University of Innsbruck, Universitätsstraße 15, A-6020 Innsbruck.
² Department of Design, Norwegian University of Science and Technology, Raufossvegen 40, 2821 Gjøvik.

Abstract

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.

Keywords: Crowdsourcing; First impression; User preference; Web design.