Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Cordeiro, M (Author) Other; Sarmento, RP (Author) Other; Brazdil, P (Author) Other; Kimura, M (Author) Other; João Gama (Author) FEP

Conference proceedings International

Title: Complex Networks and Their Applications VIII - Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019, Lisbon, Portugal, December 10-12, 2019.

Pages: 198-210

8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019

10 December 2019 through 12 December 2019

Indexing

Scopus - 2 Citations

Crossref

Other information

Authenticus ID: P-00R-FNV

DOI: 10.1007/978-3-030-36687-2_17

Abstract (EN): Discovering communities in a network is a fundamental and important problem to complex networks. Find the most influential actors among its peers is a major task. If on one side, studies on community detection ignore the influence of actors and communities, on the other hand, ignoring the hierarchy and community structure of the network neglect the actor or community influence. We bridge this gap by combining a dynamic community detection method with a dynamic centrality measure. The proposed enhanced dynamic hierarchical community detection method computes centrality for nodes and aggregated communities and selects each community representative leader using the ranked centrality of every node belonging to the community. This method is then able to unveil, track, and measure the importance of main actors, network intra and inter-community structural hierarchies based on a centrality measure. The empirical analysis performed, using two temporal networks shown that the method is able to find and tracking community leaders in evolving networks. © 2020, Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific