Abstract
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Analyzing a user's first impression of a Web site is essential for interface designers, as it is tightly related to their overall opinion of a site. In fact, this early evaluation affects user navigation behavior. Perceived usability and user interest (e.g., revisiting and recommending the site) are parameters influenced by first opinions. Thus, predicting the latter when creating a Web site is vital to ensure users? acceptance. In this regard, Web aesthetics is one of the most influential factors in this early perception. We propose the use of low-level image parameters for modeling Web aesthetics in an objective manner, which is an innovative research field. Our model, obtained by applying a stepwise multiple regression algorithm, infers a user's first impression by analyzing three different visual characteristics of Web site screenshots?texture, luminance, and color?which are directly derived from MPEG-7 descriptors. The results obtained over three wide Web site datasets (composed by 415, 42, and 6 Web sites, respectively) reveal a high correlation between low-level parameters and the users? evaluation, thus allowing a more precise and objective prediction of users? opinion than previous models that are based on other image characteristics with fewer predictors. Therefore, our model is meant to support a rapid assessment of Web sites in early stages of the design process to maximize the likelihood of the users? final approval. | |
International
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Si |
JCR
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Si |
Title
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Acm Transactions on the Web |
ISBN
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1559-1131 |
Impact factor JCR
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1,061 |
Impact info
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Datos JCR del año 2015 |
Volume
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11 |
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10.1145/3019595 |
Journal number
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1 |
From page
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1 |
To page
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25 |
Month
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ABRIL |
Ranking
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