Algorithms for Large-scale Network Analysis and the NetworKit Toolkit

The abundance of massive network data in a plethora of applications makes scalable analysis algorithms and software tools necessary to generate knowledge from such data in reasonable time. Addressing scalability as well as other requirements such as good usability and a rich feature set, the open-so...

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Bibliographic Details
Published in:arXiv.org 2022-09
Main Authors: Angriman, Eugenio, van der Grinten, Alexander, Hamann, Michael, Meyerhenke, Henning, Penschuck, Manuel
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Network analysis
Open source software
Software engineering
Workflow
Online Access:Get full text
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Summary:The abundance of massive network data in a plethora of applications makes scalable analysis algorithms and software tools necessary to generate knowledge from such data in reasonable time. Addressing scalability as well as other requirements such as good usability and a rich feature set, the open-source software NetworKit has established itself as a popular tool for large-scale network analysis. This chapter provides a brief overview of the contributions to NetworKit made by the DFG Priority Programme SPP 1736 Algorithms for Big Data. Algorithmic contributions in the areas of centrality computations, community detection, and sparsification are in the focus, but we also mention several other aspects -- such as current software engineering principles of the project and ways to visualize network data within a NetworKit-based workflow.
ISSN:2331-8422