The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/b1e7bf95-67d7-4f4e-8043-208e7f71ad84

Nasrulin, Bulat; Ishmaev, Georgy; Pouwelse, Johan (2025): Code and dataset supporting the publication: MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/b1e7bf95-67d7-4f4e-8043-208e7f71ad84.v1

Categories

• Applied Mathematics
• Other Information and Computing Sciences
• Other Economics
• Economics
• Mathematical Sciences
• Information and Computing Sciences

Keywords

Feedback Aggregation MakerDAO Reputation Sybil attack Tokenomics

Licence

BSD-3-Clause

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Bulat Nasrulin , Georgy Ishmaev , Johan Pouwelse

This repository contains code for a Sybil-tolerant reputation mechanism based on feedback. The algorithm was tested using interactions from the MakerDAO Discourse forum.

The dataset used in the paper is based on MakerDAO forum interactions and was parsed via SourceCred. It is available in the ‘dataset’ folder.

A Sybil attack on the forum is simulated within Python notebooks.

History

• 2025-03-13 first online, published, posted

Publisher

4TU.ResearchData

Format

datasets/*.gml, datasets/sourcecred/*.json, trust/*.py, *.ipynb

Associated peer-reviewed publication

MeritRank: Sybil Tolerant Reputation for Merit-based Tokenomics

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology, Distributed Systems Group