# Centrality Measures in Complex Networks: A Survey

@article{Saxena2020CentralityMI, title={Centrality Measures in Complex Networks: A Survey}, author={Akrati Saxena and Sudarshan Iyengar}, journal={ArXiv}, year={2020}, volume={abs/2011.07190} }

In complex networks, each node has some unique characteristics that define the importance of the node based on the given application-specific context. These characteristics can be identified using various centrality metrics defined in the literature. Some of these centrality measures can be computed using local information of the node, such as degree centrality and semi-local centrality measure. Others use global information of the network like closeness centrality, betweenness centrality…

## 12 Citations

Temporal Walk Centrality: Ranking Nodes in Evolving Networks

- Computer ScienceWWW
- 2022

It is shown that temporal walk centrality can identify nodes playing central roles in dissemination processes that might not be detected by related betweenness concepts and other common static and temporal centrality measures.

Organizational Closeness Centralities of Workflow-Supported Performer-to-Activity Affiliation Networks

- Computer ScienceIEEE Access
- 2021

A series of formal approaches for building organizational closeness centrality measurement techniques on the specific type of affiliation networks and the ultimate implications of these analysis techniques as the performer-to-activity affiliation networking knowledge in workflow-supported organizations are discussed.

A Survey of Evolving Models for Weighted Complex Networks based on their Dynamics and Evolution

- Computer ScienceArXiv
- 2020

This chapter discusses the evolution of weighted networks and evolving models to generate different types of synthetic weighted networks, including undirected, directed, signed, multilayered, community, and core-periphery structured weighted networks.

Evolving Models for Dynamic Weighted Complex Networks

- Computer SciencePrinciples of Social Networking
- 2021

This chapter will cover the evolution of weighted complex networks and evolving models to generate different types of synthetic weighted networks, including undirected, directed, signed, multilayered, community, and core–periphery structured weighted networks.

Opportunities and challenges in partitioning the graph measure space of real-world networks

- Computer ScienceJ. Complex Networks
- 2021

The approach managed to identify well distinguishable groups of network domains and confer their relevant features, which turn out to be CND specific and not unique even at the level of individual CNDs.

The banking transactions dataset and its comparative analysis with scale-free networks

- Computer ScienceASONAM
- 2021

This work constructs a network of 1.6 million nodes from banking transactions of users of Rabobank, the first publicly shared dataset of intra-bank transactions, and highlights the unique characteristics of banking transaction networks with other scale-free networks.

Task-based Evaluation of 3D Radial Layouts for Centrality Visualization

- Computer Science
- 2021

Improvements to the 3D radial layouts that make it possible to visualize centrality measures of nodes in a graph and a human-centered evaluation are proposed in order to compare the efficiency score, the time to complete tasks and the number of clicks.

Identifying Ransomware Actors in the Bitcoin Network

- Computer ScienceMachine Learning, IOT and Blockchain Technologies & Trends
- 2021

It is shown that very local subgraphs of the known such actors are sufficient to differentiate between ransomware, random and gambling actors with 85%prediction accuracy on the test data set.

The many facets of academic mobility and its impact on scholars' career

- BusinessJournal of Informetrics
- 2022

Fake News Propagation and Mitigation Techniques: A Survey

- Computer SciencePrinciples of Social Networking
- 2021

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