Annie Lee

DATA COLLECTIONData was collected through web scraping and cleaned for consistency across fragrance, advertising, and historical sources. Machine learning and computer vision, including ChatGPT Vision, were used to explore patterns in vintage perfume advertising and prepare a research-ready dataset.
Data Description Access
Fragrantica Dataset Over 24,000 entries with notes, ratings, accords, perfumers, etc. Link
Parfumo Year of Release Counts of discontinued/current perfumes; “popular fragrance of the era”. Link
Fragrantica Notes Scraped notes + images for mapping. Link
Ad*Access (Duke) 7,000+ US/Canada print ads (1911–1955), beauty & hygiene. Link
All Ads A collection of vintage archives and recent social media posts. Link
Advertising Archives UK The advertisements are arranged by decade and can be searched by product. Many American advertisements are included. Link
GPT Vision Automate visual analysis of vintage perfume ads using ChatGPT Vision - test.py file in github Link
Key Gender Milestones Compiled list of key gender milestones from 1900 to 2025 by aggregating information from multiple web sources, including historical archives, academic databases, and cultural timelines. Link
    
CHATGPT VISIONI used ChatGPT Vision and Python to automate the analysis of hundreds of vintage perfume advertisements. By prompting the model to identify visual attributes such as perceived gender, facial expressions, poses, mood, and interactions, I generated a structured dataset that enabled large-scale analysis of how gender representation in perfume advertising evolved over time.




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