became a cultural phenomenon as the first decentralized cryptocurrency. Nakamoto

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became a cultural phenomenon as the first decentralized cryptocurrency. Nakamoto

became a cultural phenomenon as the first decentralized cryptocurrency. Nakamoto created 21 million Bitcoins which could be “mined” and used as currency around the world. The value of a single bitcoin began at $0.01 and the current value is around $52,000.
Despite its invention occurring 16 years ago, the true identity of Nakamoto is unknown and highly contested. The three most popular theories are
Dorian Nakamoto (referred to as Dorian to distinguish him from Satoshi Nakamoto)
Hal Finney (referred to as Finney)
Nick Szabo (referred to as Szabo)
In this project, you will need to
Do some research on the invention of Bitcoin and make your own hypothesis as to who really invented it.
Find writing samples (from emails, articles, essays, etc.) or code samples (from computer programs) for the candidates: Dorian, Finney, and Szabo. Here are a few possible sites to use – but please don’t limit yourself to these.There is writing from Satoshi Nakamoto here: https://satoshi.nakamotoinstitute.org/
Dorian: https://www.reddit.com/r/Bitcoin/comments/3nzqqh/h…
Finney: https://fennetic.net/irc/finney.org/~hal/home.html
Szabo: https://www.fon.hum.uva.nl/rob/Courses/Information… and https://web.archive.org/web/20160709091851/http:/s…
Consider whether you want to compare writing samples of code samples, but probably not both in the same analysis.
Adapt the Python code that we use in class for stylometry analysis of the Federalist papers. Use your adapted code to give a chi-square score of similarity between the writings of Satoshi Nakamoto and each of the three candidates, in terms of word frequency, after omitting “boring” words like “and” and “the”. See this folder for a template for the stylometry analysis code.
Find the most likely candidate based on your analysis.
Discuss if this result agrees with your original hypothesis and/or public consensus.
Discuss weaknesses of your source data and your algorithm and how it might be improved.

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