"Superfan"? Cute. Try running data analysis on 13K+ Doechii videos. 😉

If you haven’t watched Doechii’s Tiny Desk performance yet… seriously, what are you waiting for? It’s a must-see. And if the title of this newsletter didn’t already give it away—I’m a fan of her Alligator Bites Don’t Heal album. It’s been on repeat.

I won’t pretend I was an early fan, but it’s undeniable—Doechii is having a lot of momentum. With her recent feature on ExtraL and the release of Anxiety, she’s reaching new audiences fast.

That got me thinking—so, naturally, I went down a data rabbit hole. I analyzed over 13,000 Doechii-related YouTube videos uploaded since January 1st to see what patterns would emerge. My goal? To answer two key questions:

1️⃣ What kinds of tags are people using on these videos? Are there recurring themes, and how are creators optimizing for SEO?
2️⃣ Can I connect the dots between commenters across multiple videos? Which uploads have the strongest links based on shared audiences?

Just a quick reminder—this newsletter is all about pushing the limits of publicly available data. Could I do more with full access to streaming and social insights? Absolutely. Would it change my approach? Probably.

The beauty of this method is that it isn’t just for Doechii. These deep dives can be applied to any artist, market, or genre.

Let’s get into it. 🚀

Clusters in Doechii’s YouTube Hashtag Network

Every artist leaves a digital footprint, and on YouTube, that footprint is shaped by hashtags and keywords. Analyzing these tags reveals how an artist is being talked about, what trends are forming, and where audience engagement is strongest.

For this edition, I analyzed hashtag data from over 13,000 YouTube videos mentioning Doechii, all uploaded between January 1st and last week. By tracking which tags appear together, I built a network graph—a map of keyword connections—revealing how different themes cluster around her name.

Here’s what stood out 👇

1️⃣ “Anxiety” – The Breakout Song Cluster

Doechii’s latest track, Anxiety, has quickly built its own keyword ecosystem. The song is linked to hashtags like:

👉 doechii anxiety, anxiety lyrics, anxiety reaction, somebody’s watching me, my anxiety, keep on trying me, sleepy hallow anxiety.

2️⃣ Doechii’s Core Music & Performance Cluster

These tags highlight which songs and performances are gaining traction:

👉 doechii, doechii denial is a river, doechii live, tiny desk, genius open mic, doechii tour.

This signals that fans are actively searching for her live performances.

3️⃣ Hip-Hop & Beat-Making Community

Doechii is making an impact among producers, with many creating beats in her style:

👉 doechii type beat, kendrick lamar type beat, jid type beat, boom bap, trap beat, freestyle beat.

This signals her influence in hip-hop production circles—an indicator that her sound is inspiring a creative wave.

4️⃣ Reaction & Commentary Cluster

Strong reaction video engagement often signals virality. These tags show that YouTube creators are jumping on her content for engagement:

👉 reaction video, voice coach reacts, doechii reaction, first reaction, tryna silence me and my anxiety.

5️⃣ TikTok & Viral Trends Cluster

TikTok remains a major driver of music discovery. If these tags cluster around a song, it’s a strong sign that it’s spreading beyond YouTube:

👉 fyp, tiktok dance, trending, viral, challenge song.

6️⃣ Doechii & Other Artists

These tags show how listeners categorize her—who they associate her with

👉 kendrick lamar, sza, nicki minaj, tyler the creator, doechii x jid type beat, doechii x doja cat type beat.

If certain names keep showing up, it suggests a shared fanbase and potential crossover appeal.

7️⃣ Doechii & K-Pop Crossovers

Doechii’s collaboration with BLACKPINK’s Jennie is making waves, and the hashtag data reflects that crossover:

👉 jennie, blackpink, kpop, jennie doechii reaction, jennie rap, kpop reaction.

With K-pop’s massive global reach, this could be a strategic expansion into new fanbases.

How Are Fans Connecting Videos?

Beyond analyzing hashtags, I also looked at YouTube comments to see which videos share the strongest audience overlap. By tracking users who commented on multiple videos, I wanted to uncover whether certain uploads are more interconnected than others.

To keep the visualization clean, I focused on the videos with the strongest relationships—but there’s more beneath the surface.

Based on the clustering results and an analysis of the video tags, the main content type groups are:

1. Dance & Challenge Videos – Titles with "Who Is The Best?" and references to dance trends, challenges, and short-form content.

2. Fashion & Performance Clips – Videos related to runway shows, stylish appearances, and artistic expressions (e.g., Doechii at Schiaparelli PFW).

3. Music Videos & Live Performances – Official music videos and live music performances, including concert recordings.

4. Behind-the-Scenes & Reaction Content – Includes reactions, interviews, and behind-the-scenes footage related to artists.

5. Freestyle & Creative Sessions – Unstructured performances, such as "Swamp Session" or freestyle clips.

I appreciate you taking the time to read this—I know data isn’t always the most exciting thing to look at, but I do my best to make it as engaging as possible. If you enjoyed (or did not) this deep dive, let me know by voting in the poll below!

Until next time—where I’ll be breaking down Audius and how it tackles some of the biggest superfan concerns in the industry. 👋