Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness

Reinecke, Katharina; Yeh, Tom; Miratrix, Luke; Mardiko, Rahmatri; Zhao, Yuqing; Liu, Jenny; Gajos, Krzysztof Z.

doi:10.1145/2470654.2481281

Cited by 228 publications

(228 citation statements)

References 35 publications

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“…Current computational models for quantifying aesthetics are based on low level features of design elements [28,99,197,198]. We believe that both outcomes of this work, the inferred color semantics and the application of the LDA-dual model to color semantics can leverage the current models of quantifying aesthetics.…”

Section: Quantifying Aestheticsmentioning

confidence: 91%

“…Although some studies in HCI investigate the role of colors in aesthetics and usability [13,17,26,48,77,[92][93][94][95][96][97][98][99][100][101][102][103] and performance of the user [78,104,105], the notion of color semantics has been barely addressed. As an example, consider a scenario in which users are surfing the Web for a "massage therapy" website.…”

Section: Color Semantics In Hcimentioning

confidence: 99%

“…We believe that color semantics is a legitimate challenge to be addressed in various venues of HCI: in automatic design [107][108][109][110][111][112], design by example [113][114][115][116], design grammar [117], design of user interaction [118][119][120][121][122][123][124][125], quantifying aesthetics of design [26,28,99], user experience design [126][127][128][129][130][131][132], and color design [40,[133][134][135][136][137][138]. For instance, in design by example, although users are supported by a pool of designs and some mechanisms help them choose their preferred designs [116], there is no well-defined interaction to understand the user's purpose of designs or what color combinations should be selected from their preferred designs.…”

Section: Color Semantics In Hcimentioning

confidence: 99%

“…For instance, Lin et al [78] employ crowdsourcing to confirm improvement in their subjects' performance when color semantics is utilized in information visualization. Reineke et al [99,160] utilize crosscultural crowdsourcing to study some perceived aesthetics aspects of visual complexity and colorfulness in a dataset of website designs. Inspired by their online setup, we designed the demographical aspects of our crowdsourcing experiments.…”

Section: User Studies Via Crowdsourcingmentioning

confidence: 99%

“…For the demography questions, we borrowed a setup similar to the one in [99]. For the color semantics, we designed two sets of 12 questions.…”

Section: Formative Studymentioning

confidence: 99%

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Quantifying Aesthetics of Visual Design Applied to Automatic Design

Jahanian

2016

Springer Theses

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Section: Quantifying Aestheticsmentioning

confidence: 91%

Section: Color Semantics In Hcimentioning

confidence: 99%

Section: Color Semantics In Hcimentioning

confidence: 99%

Section: User Studies Via Crowdsourcingmentioning

confidence: 99%

“…For the demography questions, we borrowed a setup similar to the one in [99]. For the color semantics, we designed two sets of 12 questions.…”

Section: Formative Studymentioning

confidence: 99%

See 3 more Smart Citations

Quantifying Aesthetics of Visual Design Applied to Automatic Design

Jahanian

2016

Springer Theses

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Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

Brewer

2023

Asso for Info Science & Tech

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Evaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality.

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Getting away from death fear: How disease threat drives consumers' colorfulness seeking

Yi,

Luo,

Wang

et al. 2023

J of Consumer Behaviour

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The COVID‐19 pandemic had significant effects on the health and wellbeing of people worldwide. However, in the post‐epidemic era, we still know very little about how disease threat shapes consumer psychology and behavior. To fill this gap in knowledge, the present study explores the effect of disease threat on a particular sensory preference of consumers, that is, a preference for colorfulness. Based on compensatory consumption theory, we propose the following: (1) consumers prefer colorful products and brand logos to compensate for both disease threat and chronically perceived disease threat; (2) the underlying mechanism for this effect is death‐related thoughts, in that disease threat leads to more death‐related thoughts, which in turn enhance colorfulness seeking; (3) the impact of disease threat on consumers' colorfulness seeking diminishes among high sensation seekers. A set of four studies, adopting both lab and survey methods, using various manipulations and measures, and testing diverse samples, provide convergent evidence for these hypotheses. Moreover, six alternative explanations were ruled out to further elucidate the psychological process under examination in this study. This paper contributes to the literature on consumer behavior, sensory marketing, terror management theory, and compensatory consumption. Implications of these findings are discussed.

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Predicting users' first impressions of website aesthetics with a quantification of perceived visual complexity and colorfulness

Cited by 228 publications

References 35 publications

Quantifying Aesthetics of Visual Design Applied to Automatic Design

Quantifying Aesthetics of Visual Design Applied to Automatic Design

Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

Getting away from death fear: How disease threat drives consumers' colorfulness seeking

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