A Wolfram Framework for NFT Analytics
Author
Kai Harris
Title
A Wolfram Framework for NFT Analytics
Description
Using a custom API to connect to opensea.io and analyse Blockchain Data
Category
Essays, Posts & Presentations
Keywords
NFT, Data Science, ML, Graph Visualisation
URL
http://www.notebookarchive.org/2021-07-6h3nfar/
DOI
https://notebookarchive.org/2021-07-6h3nfar
Date Added
2021-07-14
Date Last Modified
2021-07-14
File Size
3.49 megabytes
Supplements
Rights
Redistribution rights reserved
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WOLFRAM SUMMER SCHOOL 2021
A Wolfram Framework for NFT Analytics
A Wolfram Framework for NFT Analytics
Kai Harris
The idea behind this project is to design a set of tools to help visualise and analyse NFT market behaviour . The marketplace on [ https://opensea.io/ ] will be our testing - ground .
API: Function(s) that handle database interactions, usually in the context of networks.
NFT: Type of contract on a Turing complete Blockchain.
CryptoPunks: Oldest collection of NFTs on the Ethereum blockchain.
API: Function(s) that handle database interactions, usually in the context of networks.
NFT: Type of contract on a Turing complete Blockchain.
CryptoPunks: Oldest collection of NFTs on the Ethereum blockchain.
Designing an API
Here we look at the page [ https://docs.opensea.io/reference ] in order to learn how to create a fully functional set of API connectors between the local machine and the OpenSea Server, so that we can request data from their database and do analytics on it and then use wolfram in-builts to do explorations on the data. Included are functions with examples on how to use them, and a larger more interesting example at the end of the chapter.
API Function Parameters
API Function Parameters
General Functions
General Functions
Example - Twitter Analytics: Buzzwords
Example - Twitter Analytics: Buzzwords
Creating a CryptoPunk Database
Here we outline a process to create a set of large databases so we have local access to image data and trade data of the cryptopunks, who are a collection of 10000 NFTs. They are the original NFT’s on the Ethereum blockchain and so will serve as a good test-case for the API functions. Included are some snapshots to show what each database looks like without having to download the files. If you would like to download the databases, they can be pulled from these addresses.
assetsDatabaseHyperlink=
https://www.wolframcloud.com/obj/0.kai.rharris/Published/assetsFullOrdered.wl
eventsDatabaseHyperlink=
https://www.wolframcloud.com/obj/0.kai.rharris/Published/CleanFULLEventsOrdered.wl
Events
Events
Events Snapshot
Events Snapshot
Assets
Assets
Assets Snapshot
Assets Snapshot
Using the Database
Now that we have a large database we want to use it to represent the data in a human understandable way. The following chapter is all about exploring this data and trying to make sense out of it. Further explanations are included within.
General NFT interest tracking over time
General NFT interest tracking over time
Transaction graph: successful trades
Transaction graph: successful trades
Machine Learning: price prediction based on image composition
Machine Learning: price prediction based on image composition
Wider Scope
The NFT space is young, born in 2017. Who knows where it will go. In terms of this project, here are some thoughts about the future of the tech.
Whats next?
Whats next?
Index Tracker
Index Tracker
◼
A useful extension of this project would be an interactive index tracker using dynamic market data.This could then be utilised in some sort of an NFT exchange hub.Of course, the bottle neck is the speed of Ethereum network transactions. As blockchains become more optimised, perhaps it will be possible to create a low-latency trading platform for NFTs on newer technology.
Acknowledgment
Acknowledgment
Big thanks to Christian Pasquel, who schooled me on database cleaning techniques among other things; Jesse Friedman, who seems to know everything about Mathematica and answered almost all of my dumb questions; the TA’s who provided endless answers to many of us the rest of the time; the other students, for making this an awesome experience; Stephen himself, for providing much needed insight into a particularly odd personal dilemma of mine; and Danielle and Erin for gluing the rest of it all together!
Cite this as: Kai Harris, "A Wolfram Framework for NFT Analytics" from the Notebook Archive (2021), https://notebookarchive.org/2021-07-6h3nfar
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