Can Stylized Products Generated by AI Better Attract User Attention? Using Eye-Tracking Technology for Research

The emergence of AIGC has significantly improved design efficiency, enriched creativity, and promoted innovation in the design industry. However, whether the content generated from its own database meets the preferences of target users still needs to be determined through further testing. This study investigates the appeal of AI-generated stylized products to users, utilizing 12 images as stimuli in conjunction with eye-tracking technology. The stimulus is composed of top-selling gender-based stylized Bluetooth earphones from the Taobao shopping platform and the gender-based stylized earphones generated by the AIGC software GPT4.0, categorized into three experimental groups. An eye-tracking experiment was conducted in which 44 participants (22 males and 22 females, mean age = 21.75, SD = 2.45, range 18–27 years) observed three stimuli groups. The eye movements of the participants were measured while viewing product images. The results indicated that variations in stimuli category and gender caused differences in fixation durations and counts. When presenting a mix of the two types of earphones, the AIGC-generated earphones and earphones from the Taobao shopping platform, the two gender groups both showed a significant effect in fixation duration with F (2, 284) = 3.942, p = 0.020 < 0.05, and η = 0.164 for the female group and F (2, 302) = 8.824, p < 0.001, and η = 0.235 for the male group. They all had a longer fixation duration for the AI-generated earphones. When presenting exclusively the two types of AI-generated gender-based stylized earphones, there was also a significant effect in fixation duration with F (2, 579) = 4.866, p = 0.008 < 0.05, and η = 0.129. The earphones generated for females had a longer fixation duration. Analyzing this dataset from a gender perspective, there was no significant effect when the male participants observed the earphones, with F (2, 304) = 1.312 and p = 0.271, but there was a significant difference in fixation duration when the female participants observed the earphones (F (2, 272) = 4.666, p = 0.010 < 0.05, and η = 0.182). The female participants had a longer fixation duration towards the earphones that the AI generated for females.

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Publication Details

Journal
Applied Sciences
Published
2024-09-02
DOI
https://doi.org/10.3390/app14177729
Citations
4
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
1.49
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article

Can Stylized Products Generated by AI Better Attract User Attention? Using Eye-Tracking Technology for Research

Chen Chen, Yunjing Tang
4 citations
Applied Sciences
Gaze Tracking and Assistive Technology
1.49
article

Can Stylized Products Generated by AI Better Attract User Attention? Using Eye-Tracking Technology for Research

Chen Chen, Yunjing Tang
article en
4 citations

Abstract

The emergence of AIGC has significantly improved design efficiency, enriched creativity, and promoted innovation in the design industry. However, whether the content generated from its own database meets the preferences of target users still needs to be determined through further testing. This study investigates the appeal of AI-generated stylized products to users, utilizing 12 images as stimuli in conjunction with eye-tracking technology. The stimulus is composed of top-selling gender-based stylized Bluetooth earphones from the Taobao shopping platform and the gender-based stylized earphones generated by the AIGC software GPT4.0, categorized into three experimental groups. An eye-tracking experiment was conducted in which 44 participants (22 males and 22 females, mean age = 21.75, SD = 2.45, range 18–27 years) observed three stimuli groups. The eye movements of the participants were measured while viewing product images. The results indicated that variations in stimuli category and gender caused differences in fixation durations and counts. When presenting a mix of the two types of earphones, the AIGC-generated earphones and earphones from the Taobao shopping platform, the two gender groups both showed a significant effect in fixation duration with F (2, 284) = 3.942, p = 0.020 < 0.05, and η = 0.164 for the female group and F (2, 302) = 8.824, p < 0.001, and η = 0.235 for the male group. They all had a longer fixation duration for the AI-generated earphones. When presenting exclusively the two types of AI-generated gender-based stylized earphones, there was also a significant effect in fixation duration with F (2, 579) = 4.866, p = 0.008 < 0.05, and η = 0.129. The earphones generated for females had a longer fixation duration. Analyzing this dataset from a gender perspective, there was no significant effect when the male participants observed the earphones, with F (2, 304) = 1.312 and p = 0.271, but there was a significant difference in fixation duration when the female participants observed the earphones (F (2, 272) = 4.666, p = 0.010 < 0.05, and η = 0.182). The female participants had a longer fixation duration towards the earphones that the AI generated for females.

Applied SciencesVol. 14(17)
Nanjing Forestry University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Gaze Tracking and Assistive Technology
1.49
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