Understanding consumer perception and acceptance of AI art through eye tracking and Bidirectional Encoder Representations from Transformers-based sentiment analysis

Understanding consumer perception and acceptance of AI art through eye tracking and Bidirectional Encoder Representations from Transformers-based sentiment analysis

This study investigates public perception and acceptance of AI-generated art using an integrated system that merges eye-tracking methodologies with advanced bidirectional encoder representations from transformers (BERT)-based sentiment analysis. Eye-tracking methods systematically document the v...

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Bibliographic Details
Main Authors: Tao Yu, Junping Xu, Younghwan Pan
Format: Article
Language:English
Published: Bern Open Publishing 2024-12-01
Series:Journal of Eye Movement Research
Subjects:
AI Art
Eye Tracking
Sentiment Analysis
Consumer Perception
Visual Attention
Emotion Analysis
Online Access:https://bop.unibe.ch/JEMR/article/view/11463
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https://bop.unibe.ch/JEMR/article/view/11463

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