Eye-Tracking Data on Wine Tourism Ads from Travel Platforms

Eye-tracking research analyzes the effectiveness of visual wine tourism advertising on digital travel platforms. The 701.5 KB dataset, authored by JJ C-H and last updated in May 2026, likely contains metrics on visual attention, processing, and ad recall. It studies images featuring human presence, wineries, and vineyards on platforms like Airbnb, Booking.com, and Tripadvisor.

Use Cases

• Train attention prediction models based on visual features like human presence and vineyard imagery.
• Analyze ad recall performance based on different image categories used in the study.
• Benchmark visual processing metrics for tourism advertisements across platforms like Airbnb and Tripadvisor.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Research focuses on a specific, contemporary domain of digital travel advertising.
• The 701.5 KB size suggests a focused, manageable dataset for analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is stored as a PDF, which may complicate direct computational analysis.

Provenance

Source

figshare

Collection Method

Collected via eye-tracking experiments on digital travel platforms.

Freshness

Last updated 2026-05-26 11:27:15; freshness should be verified.