Leveraging local h-index to identify and rank influential spreaders in networks

Qiang Liu, Yu-Xiao Zhu, Yan Jia, Lu Deng, Bin Zhou, Jun-Xing Zhu and Peng Zou

Physica A: Statistical Mechanics and its Applications, 2018, vol. 512, issue C, 379-391

Abstract: Identifying influential nodes in complex networks has received increasing attention for its great theoretical and practical applications in many fields. Some classical methods, such as degree centrality, betweenness centrality, closeness centrality, and coreness centrality, were reported to have some limitations in detecting influential nodes. Recently, the famous h-index was introduced to the network world to evaluate the spreading ability of the nodes. However, this method always assigns too many nodes with the same value, which leads to a resolution limit problem in distinguishing the real influences of these nodes. In this paper, we propose a local h-index centrality (LH-index) method to identify and rank influential nodes in networks. The LH-index method simultaneously takes into account of h-index values of the node itself and its neighbors, which is based on the idea that a node connecting to more influential nodes will also be influential. Experimental analysis on stochastic Susceptible–Infected–Recovered (SIR) model and several networks demonstrates the effectivity of the LH-index method in identifying influential nodes in networks.

Keywords: Complex networks; Influential nodes; Local h-index centrality; SIR model (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118309932
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:512:y:2018:i:c:p:379-391

DOI: 10.1016/j.physa.2018.08.053

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().