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

Data in brief, 2024-02, Vol.52, p.109976-109976, Article 109976 [Tạp chí có phản biện]

2023 ;2023 Published by Elsevier Inc. ;2023 Published by Elsevier Inc. 2023 ;ISSN: 2352-3409 ;EISSN: 2352-3409 ;DOI: 10.1016/j.dib.2023.109976 ;PMID: 38287953

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  • Nhan đề:
    Dataset of user evaluations of prototypicality, aesthetics, usability and trustworthiness of homepages of banking, e-commerce and university websites
  • Tác giả: Miniukovich, Aliaksei ; Figl, Kathrin
  • Chủ đề: Crowdsourcing ; Data ; First impression ; User preference ; Web design
  • Là 1 phần của: Data in brief, 2024-02, Vol.52, p.109976-109976, Article 109976
  • Mô tả: 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.
  • Nơi xuất bản: Netherlands: Elsevier Inc
  • Ngôn ngữ: English
  • Số nhận dạng: ISSN: 2352-3409
    EISSN: 2352-3409
    DOI: 10.1016/j.dib.2023.109976
    PMID: 38287953
  • Nguồn: Open Access: DOAJ Directory of Open Access Journals
    Open Access: PubMed Central
    ROAD
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