Cryptoasset Analytics Tutorial

April 26, 2022 2pm CET — Online, part of the International World Wide Web Conference 2022

Photo by Romain Lohezic on Unsplash


This is a hands on tutorial (3h) on cutting-edge cryptoassetanalytics systems and tools for analyzing cryptoasset ecosystems. It targets novice and moderately skilled users with a basic understanding of cryptocurrencies like Bitcoin and Ethereum, and assumes basic coding skills in Python. The tutorial will gently introduce the fundamental concepts behind cryptoassets (0.5h), then focuson analyzing UTXO-model ledgers like Bitcoin (1h) and account-model ledgers like Ethereum (1h), before providing an outlook on emerging trends like Decentralized Finance (0.5h). Throughout the tutorial, attendees will work with open-source tools like GraphSense, ethereum-etl and Jupyter notebooks and work on data associated with real use cases.


This tutorial aims to teach the audience how to use cutting-edgecryptoasset analytics systems, tools and methods for analyzing various aspects of cryptoasset ecosystems. It targets novice and moderately skilled users and features for subsequent parts:

  • Cryptoassets and Blockchain 101 (0.5h)(Slides here)
    • Fundamental concepts (Cryptoassets / Bitcoin)
    • Transactions / Blocks / Mining
  • Analyzing UTXO-Model Ledgers (1h)(Slides here)
    • Data extraction
    • Network abstractions
    • Practical use case: analyzing sextortion payments
    • Usage of the GraphSense platform
  • Analyzing Account-Model Ledgers (1h)(Slides here)
    • Data extraction
    • Network and data types
    • Practical use case: visual analytics and NFT wash trading
  • Outlook (0.5h)(Slides here)
    • Hot topics, challenges
    • Open discussion

The tutorial will contain various live exercises that will be performed with Python and Jupyter notebooks. Please see the associated repository for more information. You may want to setup your local environment prior to the tutorial.

For the third part on analyzing account model ledgers, attendees are advised to sign up with and get a free endpoint URL to an Ethereum archive node.


Friedhelm Victor

Friedhelm Victor is a PhD candidate at Technische Universität Berlin with several years of experience analyzing financial transaction networks in both traditional finance and modern cryptoasset networks. Friedhelm holds a dual master’s degree inComputer Science from Technische Universität Berlin and Korea Advanced Institute of Science and Technology (KAIST). His research interests are network analysis, fraud detection, privacy andanonymity, and his current focus are cryptoasset networks.

Bernhard Haslhofer

Bernhard Haslhofer leads the CryptoFinance research group at the Complexity Science Hub Vienna and works as an external lecturer at the Technical University of Vienna. Bernhard obtained his doctorate from the University of Vienna in Computer Science and also received his master’s degree in Economics and Computer Science. Before joining CSH, he led the data science research field at the AIT Austrian Institute of Technology. He also worked as a PostDoc at Cornell Information Science and as an assistant professor at theUniversity of Vienna. His research focuses on finding and applying quantitative data science methods for gaining new insights from large-scale, connected datasets. Currently, his main research focus is in the field of Cryptoassets Analytics.


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