youtube-vape-classification

This skill uses supervised machine learning to automatically analyze e-cigarette videos on YouTube, classifying video themes (product reviews, instructions, vape tricks), featured products, channel types (enthusiasts, retailers, brands), and sales strategies including discounts and external purchase links. The system was trained on 3,830 English-language videos and achieves up to 0.87 F1 score accuracy. It processes video metadata to predict four distinct models, enabling researchers and regulators to understand how e-cigarette products are promoted to youth audiences on social media. This tool supports public health research by quantifying marketing tactics, engagement metrics, and product promotion patterns across YouTube's vaping content.

[{"step":"Gather YouTube video URLs for analysis. Use tools like YouTube Data API, browser extensions (e.g., Video DownloadHelper), or manually copy URLs from search results or channels.","tip":"Focus on videos with high engagement (views, likes) or from channels with known vape-related content to maximize relevance."},{"step":"Paste the video URL into the prompt template and execute the classification. For batch processing, use a tool like Google Apps Script or Python with the YouTube API to automate URL collection and AI analysis.","tip":"For large datasets, pre-filter videos using keywords like 'vape', 'e-cig', 'cloud chasing', or 'e-liquid' to reduce irrelevant content."},{"step":"Review the structured report for key insights: product mentions, marketing tactics, and compliance risks. Use the confidence scores to prioritize follow-up actions.","tip":"Cross-reference product names with databases like the FDA's [e-cigarette product list](https://www.fda.gov/tobacco-products/products-ingredients-components/ecigarettes-list-products-ingredients-components) to verify legitimacy."},{"step":"Take action based on findings. For marketers, use insights to identify competitors, influencers, or gaps in vape product promotion. For regulators, flag non-compliant content for review.","tip":"Combine this skill with sentiment analysis tools (e.g., MonkeyLearn) to assess viewer reactions to vape-related content."},{"step":"Store results in a database or spreadsheet for trend analysis. Track recurring products, uploaders, or marketing strategies over time to identify patterns.","tip":"Use tools like Airtable or Google Sheets with AI integrations (e.g., Zapier + AI) to automate data storage and visualization."}]