Ereiyes, Kayhan2024-07-122024-07-122021978-1-6654-0759-510.1109/IISEC54230.2021.96723342-s2.0-85125360048https://doi.org/10.1109/IISEC54230.2021.9672334https://hdl.handle.net/20.500.12415/73822nd International Informatics and Software Engineering Conference (IISEC) - Artificial Intelligence for Digital Transformation -- DEC 16-17, 2021 -- Ankara, TURKEYComplex networks are large and analysis of these networks require significantly different methods than small networks. Parallel processing is needed to provide analysis of these networks in a timely manner. Graph centrality measures provide convenient methods to assess the structure of these networks. We review main centrality algorithms, describe implementation of closed centrality in Python and propose a simple parallel algorithm of closed centrality and show its implementation in Python with obtained results.eninfo:eu-repo/semantics/closedAccessComplex NetworkCloseness CentralityBetweenness CentralityParallel AlgorithmConference ObjectN/AWOS:000841548300001N/A