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Computing Top-k Closeness Centrality in Fully-dynamic Graphs., , , and . ALENEX, page 21-35. SIAM, (2018)Algorithms for Large-Scale Network Analysis and the NetworKit Toolkit., , , , and . Algorithms for Big Data, volume 13201 of Lecture Notes in Computer Science, Springer, (2022)Scalable Algorithms for the Analysis of Massive Networks. HU Berlin, Germany, (2022)base-search.net (fthuberlin:oai:edoc.hu-berlin.de:18452/25013).Group-Harmonic and Group-Closeness Maximization - Approximation and Engineering., , , , , and . CoRR, (2020)Group Centrality Maximization for Large-scale Graphs., , , , , and . ALENEX, page 56-69. SIAM, (2020)Guidelines for Experimental Algorithmics: A Case Study in Network Analysis., , , , , , and . Algorithms, 12 (7): 127 (2019)Interactive Visualization of Protein RINs using NetworKit in the Cloud., , , , and . IPDPS Workshops, page 255-264. IEEE, (2022)Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis., , , and . ESA, volume 173 of LIPIcs, page 6:1-6:24. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2020)New Approximation Algorithms for Forest Closeness Centrality - for Individual Vertices and Vertex Groups., , , and . SDM, page 136-144. SIAM, (2021)Computing Top-k Closeness Centrality in Fully-dynamic Graphs., , , and . CoRR, (2017)