How to attribute credit if you must

Meiklejohn, Luke S

How to attribute credit if you must

Master Thesis

2021

Abstract

Data ownership is of fundamental importance in the digital economy of today. Commercializing academic research, whilst maintaining ownership of it, is a task that can now be accomplished due to the strengths of blockchain technology, which allows data to be registered, made unique, and traced to its origins. We propose a blockchain use-case for licencing academic research, based off an academic project named UniCoin. In this thesis, we discuss how to fairly attribute credit between all sources of knowledge that contribute to new pieces of academic research, using citation network analysis and centrality measures. Katz centrality, in-degree centrality, and PageRank are three potentially useful centrality measures, with varying results: these are compared using case studies based on three papers co-authored by Andrei Shleifer. We use these centrality measures to guide how to fairly attribute credit, and thus how to distribute licencing revenues generated through UniCoin.