Exploring Human Images in Website Design: A Multi-Method Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Effective visual design of e-commerce websites enhances website aesthetics and emotional appeal for the user. To gain insight into how Internet users perceive human images as one element of website design, a controlled experiment was conducted using a questionnaire, interviews, and eye-tracking methodology. Three conditions of human images were created including human images with facial features, human images without facial features, and a control condition with no human images. It was expected that human images with facial features would induce a user to perceive the website as more appealing, having warmth or social presence, and as more trustworthy. In turn, higher levels of image appeal and perceived social presence were predicted to result in trust. All expected relationships in the model were supported except no direct relationship was found between the human image conditions and trust. Additional analyses revealed subtle differences in the perception of human images across cultures (Canada, Germany, and Japan). While the general impact of human images seems universal across country groups, based on interview data four concepts emergedâaesthetics, symbolism, affective property, and functional propertyâwith participants from each culture focusing on different concepts as applied to website design. Implications for research and practice are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it