Open AccessEfficiency centrality in time-varying graphs
Author(s) -
Péter Marjai,
Attila Kiss
Publication year - 2020
Publication title -
acta universitatis sapientiae. informatica
Language(s) - English
Resource type - Journals
eISSN - 2066-7760
pISSN - 1844-6086
DOI - 10.2478/ausi-2020-0001
Subject(s) - betweenness centrality , centrality , computer science , closeness , katz centrality , network controllability , network theory , measure (data warehouse) , complex network , degree (music) , theoretical computer science , network science , algorithm , data mining , mathematics , combinatorics , physics , mathematical analysis , world wide web , acoustics
One of the most studied aspect of complex graphs is identifying the most influential nodes. There are some local metrics like degree centrality, which is cost-effiective and easy to calculate, although using global metrics like betweenness centrality or closeness centrality can identify influential nodes more accurately, however calculating these values can be costly and each measure has it’s own limitations and disadvantages. There is an ever-growing interest in calculating such metrics in time-varying graphs (TVGs), since modern complex networks can be best modelled with such graphs. In this paper we are investigating the effectiveness of a new centrality measure called efficiency centrality in TVGs. To evaluate the performance of the algorithm Independent Cascade Model is used to simulate infection spreading in four real networks. To simulate the changes in the network we are deleting and adding nodes based on their degree centrality. We are investigating the Time-Constrained Coverage and the magnitude of propagation resulted by the use of the algorithm.