It takes input of selected NFT projects, and suggests others.
Suggestions are distilled from pure transaction data; patterns in a
collective.
Collective Filter is a toy, an experiment, for fun. It
should not be regarded as an oracle for any good advice, whether financial or aesthetic
or dietary.
How does it work?
Collective Filter uses a statistical model built from transaction data to suggest
other NFT projects.
It's built from a subset of data, just a snapshot, so it won't
have all your favorite projects. Currently, it only contains data from Ethereum
mainnet,
and is based on 100,000 transactions from 1,000 projects. Using this data snapshot, the
model maps your selected interests to other projects. These suggested projects
reflect collective activity of other collectors. Credits:
Data from
Etherscan,
OpenSea.
Statistical modeling & coding by
Takens
Theorem.
Some delightful goodies by
Bulma,
math.js,
Animate.css.
How do I use it?
See here
for a demonstration.
I do not require or use any wallet connections, though I may add this in the future.
To start, click the buttons below 'Select.' You can mouseover these buttons to get
a quick description. For example, 'tx' lists projects by transactions in the current
data snapshot. When the left side populates with
projects, you can select them with the
plus button. This immediately generates suggestions
at the right. That's it! Feel free to click around.
A few other notes. You can exclude projects from your use by clicking the
red button on
the bottom right of the results. You can also click on various explorers for the projects
as shown in the small button icons. There are a few other details,
feel free to click around and see.
Is this any good?
This is a little experiment. Collective Filter uses a snapshot of NFT
transaction data to
build a statistical model.
I did little to no direct curation of the output. Sometimes Collective Filter may work quite
well,
sometimes results might surprise.
Importantly I welcome
feedback here!
Warning: Creators and collectors may be disappointed by the output.
But in blockchain, connections across favorite projects are subject to data
trends not under our control. Sometimes the model will err. Other times, it will
surprise with an unwelcome reality.
Can I save my recommendations?
I have implemented one single save feature: You can click the save checkbox
in ⚙ options and opt-in to store your favorites list in
localStorage.
So when you close this window or refresh the page, Collective Filter will
hold onto your favorites. However everything else is reset, including all
selected projects, suggestions and exclusions. I welcome feature requests if
you have another preference for this.
What about next features?
I have many updates already coded up. These include NFT projects on other chains,
different statistical models and more. If you have favored improvements or suggestions,
I very much welcome them
here. If
you'd like
to encourage me to keep going feel free to
donate
here
or pick up a primary item from
my other
creative
projects.
Are you advertising or boosting?
In short, no, not at all. The model uses raw data and I do not highlight or transform
the data with any specific goal other than to express the underlying collective trends.
An important caveat though: Any model is based on a sample of data curated
with projects I've either collected or found interesting over the years.
For this reason, some projects may sometimes appear at the top more than others. This was
not for the purpose of boosting, but reveals the creator's own interests. An important
disclaimer to wrap up:
This project has no mint.
It's just curious data.