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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.03504 |
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| _version_ | 1866909129474310144 |
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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 |