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Main Authors: Dietl, Marcell, Gemünd, Andre, Oeltz, Daniel, Thiele, Felix M., Werner, Christian
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.03504
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author Dietl, Marcell
Gemünd, Andre
Oeltz, Daniel
Thiele, Felix M.
Werner, Christian
author_facet Dietl, Marcell
Gemünd, Andre
Oeltz, Daniel
Thiele, Felix M.
Werner, Christian
contents In this report, we introduce a novel approach to visualize extremely large graphs efficiently. Our method combines two force-directed algorithms, Kamada-Kawai and ForceAtlas2, to handle different graph components based on their node count. Additionally, we suggest utilizing the Fast Multipole method to enhance the speed of ForceAtlas2. Although initially designed for analyzing bitcoin transaction graphs, for which we present results here, this algorithm can also be applied to other crypto currency transaction graphs or graphs from diverse domains.
format Preprint
id arxiv_https___arxiv_org_abs_2403_03504
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Graph Visualization for Blockchain Data
Dietl, Marcell
Gemünd, Andre
Oeltz, Daniel
Thiele, Felix M.
Werner, Christian
Data Structures and Algorithms
Discrete Mathematics
In this report, we introduce a novel approach to visualize extremely large graphs efficiently. Our method combines two force-directed algorithms, Kamada-Kawai and ForceAtlas2, to handle different graph components based on their node count. Additionally, we suggest utilizing the Fast Multipole method to enhance the speed of ForceAtlas2. Although initially designed for analyzing bitcoin transaction graphs, for which we present results here, this algorithm can also be applied to other crypto currency transaction graphs or graphs from diverse domains.
title Graph Visualization for Blockchain Data
topic Data Structures and Algorithms
Discrete Mathematics
url https://arxiv.org/abs/2403.03504