2022/09/20 by Eugenio Angriman, Angriman, Eugenio, Alexander van der Grinten +7 · 2 citations
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · Psychology · #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Mental Health Research Topics #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2209.13355
openalex publication_date 2022/09/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.