H3: The Artometrics of a YouTube Dynasty

A creator profile data analysis of the H3 Podcast network — Ethan and Hila Klein's four-channel operation — built on a custom dataset assembled via the YouTube Data API v3, Wikipedia Pageviews API, and Google Trends.

What's in this repo

• h3.qmd — Quarto markdown file containing all R, SQL, and Python code, analysis, and write-up
• data/h3_master.csv — master dataset: 1,638 videos across 4 channels (filtered)
• data/h3_wikipedia.csv — Wikipedia pageview data (monthly)
• data/h3_wikipedia_daily.csv — Wikipedia pageview data (daily)
• data/h3_trends.csv — Google Trends data via gtrendsR
• data/h3_podchaser_episodes.csv — episode-level podcast data from Podchaser
• charts/chart1_era_timeline.png — monthly H3 Podcast views 2017–2026 with Frenemies and Leftovers era markers
• charts/chart2_duration_drift.png — episode duration drift by era and channel
• charts/chart3_reddit_activity.png — Reddit activity: r/h3h3productions vs r/h3snark over time

What the analysis covers

Three charts and a polyglot analysis (R + SQL + Python) working through what the data actually shows about one of YouTube's most unusual long-run careers:

1. How H3 Podcast viewership evolved across four distinct eras — and what killed each one
2. Whether episodes are getting longer, shorter, or more erratic — and what that signals about format
3. How fan sentiment on Reddit splits between the main sub and the snark sub across the same events

Read the full article

artometrics.com/h3-the-artometrics-of-a-youtube-dynasty

Data sources

• YouTube Data API v3 — video metadata, view counts, upload dates (Google Cloud project: ARTOMETRICS)
• Wikipedia Pageviews API — no key required
• Google Trends via gtrendsR R package
• Podchaser — episode-level podcast metadata

Note: Reddit JSONL source files (r/h3h3productions, r/h3snark) exceed GitHub's 100 MB file size limit and are excluded from this repo. The processed summary CSV is included at data/h3_snark_posts.csv.

Tools

• R / Quarto
• tidyverse · ggplot2 · ggrepel · ggtext · scales · lubridate · httr · jsonlite · gtrendsR
• Python (pandas · numpy) · SQL

Disclosure

This analysis is based on original data work (R / YouTube Data API v3). AI was used to assist in analysis, research, and writing.