This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Stell-R
Music discovery tool based only on mutual artistic influence
Every edge in the Stell-R graph represents a documented influence connection between ~25,000 artists, pulled from album reviews and music-history writing where one artist's name is explicitly cited in critiques of another's work. Not streaming co-listens, user similarity, or genre tags, just documented influence. My core methodology is at: Badillo-Goicoechea, E. (2025). Modeling Artist Influence for Music Selection and Recommendation: A Purely Network-Based Approach. Harvard Data Science Review
Built this just for fun and curiosity as a data scientist + music lover as Stell-R, a music discovery tool based on pure, documented influence lineage ibased on artist reviews, instead of AI / algorithmic user similarity.
How do you keep the influence edges clean when a review mentions an artist in passing rather than crediting them as an influence? Seems like that distinction matters a lot at this scale.
Finally tried tracing a few obscure threads through the graph and was impressed by how cleanly it surfaces the critic-cited lineage rather than vague genre overlap.
How do you handle cases where an artist is cited in critiques of another artist, but the citation is negative or dismissive? Does that still get logged as a direct influence edge, or is there some kind of weighting based on tone?
Looked up a few artists I know and the influence chains actually feel accurate, especially the ones connecting post-rock to krautrock. The cited review excerpts behind each link are a really nice touch for trusting the data.
About Stell-R on Product Hunt
“Music discovery tool based only on mutual artistic influence”
Stell-R was submitted on Product Hunt and earned 9 upvotes and 5 comments, placing #67 on the daily leaderboard. Every edge in the Stell-R graph represents a documented influence connection between ~25,000 artists, pulled from album reviews and music-history writing where one artist's name is explicitly cited in critiques of another's work. Not streaming co-listens, user similarity, or genre tags, just documented influence. My core methodology is at: Badillo-Goicoechea, E. (2025). Modeling Artist Influence for Music Selection and Recommendation: A Purely Network-Based Approach. Harvard Data Science Review
Stell-R was featured in Music (53.5k followers), Internet of Things (226.3k followers) and Tech (627.5k followers) on Product Hunt. Together, these topics include over 184k products, making this a competitive space to launch in.
Who hunted Stell-R?
Stell-R was hunted by Elena Badillo Goicoechea. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Stell-R stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Elena Badillo Goicoechea