mlsanityData to 7 Oct 2026

Algorithms for Large-scale Network Analysis and the NetworKit Toolkit

arXiv 2209.13355 ↗First posted 20 Sep 2022cs.SI cs.DScited by 5

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Abstract (arXiv)

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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2022.

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Citing papers per year: 2024: 3; 2025: 0; 2026: 2.

5 papers.