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Predicting Users' First Impressions of Website Aesthetics With a Quantification of Perceived Visual Complexity and Colorfulness

机译:通过量化感知到的视觉复杂性和色彩来预测用户对网站美学的第一印象

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Users make lasting judgments about a website's appeal within a split second of seeing it for the first time. This first impression is influential enough to later affect their opinions of a site's usability and trustworthiness. In this paper, we demonstrate a means to predict the initial impression of aesthetics based on perceptual models of a website's colorfulness and visual complexity. In an online study, we collected ratings of colorfulness, visual complexity, and visual appeal of a set of 450 websites from 548 volunteers. Based on these data, we developed computational models that accurately measure the perceived visual complexity and colorfulness of website screenshots. In combination with demographic variables such as a user's education level and age, these models explain approximately half of the variance in the ratings of aesthetic appeal given after viewing a website for 500ms only.
机译:用户在第一次看到网站的瞬间就做出了持久的判断。最初的印象很有影响力,后来影响了他们对站点可用性和可信赖性的看法。在本文中,我们展示了一种基于网站色彩丰富度和视觉复杂性的感知模型来预测美学初始印象的方法。在一项在线研究中,我们从548名志愿者那里收集了450个网站的色彩,视觉复杂性和视觉吸引力的评分。基于这些数据,我们开发了计算模型,该模型可以准确地测量所感知的网站屏幕截图的视觉复杂性和色彩。这些模型结合用户的受教育程度和年龄等人口统计变量,可以解释仅在浏览网站500毫秒后给出的美学吸引力等级的大约一半差异。

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