Identifying and ranking influential spreaders in complex networks by neighborhood coreness

By Joonhyun Bae. 2014

506 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/d18154a93582410b87a233f7b3977ca90c746893

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Madhumangal Pal
2. Chuang Ma
3. Kousik Das
4. Haifeng Zhang
5. Ling-Ling Ma
6. Sovan Samanta

In Statistical and Nonlinear Physics

1. Madhumangal Pal
2. Chuang Ma
3. Kousik Das
4. Haifeng Zhang
5. Ling-Ling Ma
6. Sovan Samanta

Citations in the corpus

• Identifying influential spreaders in complex networks based on gravity formula (2015, methodology): “designed a ranking method–neighborhood coreness Cnc by considering the degree and the coreness of a node simultaneously, the Cnc(i) for a node i is defined as [20]”
• Study on centrality measures in social networks: a survey (2018, background): “This measure was first introduced by Bae and Kim (2014). The basic consideration to this centrality is that a node with more links to the neighbors located in the core of the network is more powerful.”