Understanding Polkadot Through Graph Analysis: Transaction Model, Network Properties, and Insights

Hanaa Abbas*, Maurantonio Caprolu, Roberto Di Pietro

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In recent years, considerable efforts have been directed toward investigating the large amount of public transaction data in prominent cryptocurrencies. Nevertheless, aside from Bitcoin and Ethereum, little efforts have been made to investigate other cryptocurrencies, even though the market now comprises thousands, with more than 50 exceeding one billion dollars of capitalization, and some of them sporting innovative technical solutions and governance. This is the case for Polkadot, a relatively new blockchain that promises to solve the shortcomings in scalability and interoperability that encumber many existing blockchain-based systems. In particular, Polkadot relies on a novel multi-chain construction that promises to enable interoperability among heterogeneous blockchains. This paper presents the first study to formally model and investigate user transactions in the Polkadot network. Our contributions are multifolds: After defining proper and pseudo-spam transactions, we built the transaction graph based on data collected from the launch of the network, in May 2020, until July 2022. The dataset consists of roughly 11 million blocks, including 2 million user accounts and 7.6 million transactions. We applied a selected set of graph metrics, such as degree distribution, strongly/weakly connected components, density, and several centrality measures, to the collected data. In addition, we also investigated a few interesting idiosyncratic indicators, such as the accounts’ balance over time and improper transactions. Our results shed light on the topology of the network, which resembles a heavy-tailed power-law distribution, demonstrate that Polkadot is affected by the rich get richer conundrum, and provide other insights into the financial ecosystem of the network. The approach, methodology, and metrics proposed in this work, while being applied to Polkadot, can also be applied to other cryptocurrencies, hence having a high potential impact and the possibility to further research in the cryptocurrency field.

Original languageEnglish (US)
Title of host publicationFinancial Cryptography and Data Security - 27th International Conference, FC 2023, Revised Selected Papers
EditorsFoteini Baldimtsi, Christian Cachin
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages17
ISBN (Print)9783031477508
StatePublished - 2024
Event27th International Conference on Financial Cryptography and Data Security, FC 2023 - Bol, Croatia
Duration: May 1 2023May 5 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference27th International Conference on Financial Cryptography and Data Security, FC 2023


  • Cryptocurrency
  • Decentralization
  • DeFi
  • Graph Analysis
  • Multi-chain Blockchain
  • Network Science
  • Polkadot

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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