Best influential spreaders identification using network global structural properties

Abstract

Influential spreaders are the crucial nodes in a complex network that can act as a controller or a maximizer of a spreading process. For example, we can control the virus propagation in an epidemiological network by controlling the behavior of such influential nodes, and amplify the information propagation in a social network by using them as a maximizer. Many indexing methods have been proposed in the literature to identify the influential spreaders in a network. Nevertheless, we have notice that each individual network holds different connectivity structures that we classify as complete, incomplete, or in-between based on their components and density. These affect the accuracy of existing indexing methods in the identification of the best influential spreaders. Thus, no single indexing strategy is sufficient from all varieties of network connectivity structures. This article proposes a new indexing method Network Global Structure-based Centrality (ngsc) which intelligently combines existing kshell and sum of neighbors’ degree methods with knowledge of the network’s global structural properties, such as the giant component, average degree, and percolation threshold. The experimental results show that our proposed method yields a better spreading performance of the seed spreaders over a large variety of network connectivity structures, and correlates well with ranking based on an SIR model used as ground truth. It also out-performs contemporary techniques and is competitive with more sophisticated approaches that are computationally cost.

Identifying the Top-k Influential Spreaders in Social Networks: a Survey and Experimental Evaluation

“… clcy: The clustering coefficient of node y.  N(x): The neighbors of node x. Namtirtha et al [106] proposed a method that combines the degrees of neighbors and k-shell decomposition for identifying influential nodes. A node's centrality is influenced by its degree and k-shell and the degree and k-shell of its neighbors.…”

Controlling COVID-19 transmission with isolation of influential nodes

“…Influential spreaders are the critical nodes running as a controller or a maximizer of a spread process in a complex network. For instance, an epidemiological network manages the virus propagation by controlling such influential nodes behavior, which expands information propagation in a social network using them as a maximizer [6] . In the literature, multiple indexing methods have been proposed to determine the influential network spreaders [7] , [8] , [9] .…”

“…In this regard, Li et al [28] used a generalized gravity model for identifying influential spreaders in complex networks. Namtirtha et al [6] provided the best method of identifying influential spreaders based on network global structural properties. Gupta and Mishra [29] studied information dissemination in complex networks and identified a set of top-N influential nodes using network structure.…”

The role of network characteristics of the innovation spreaders in agriculture

“…This work focuses on the first and the second channels. In this regard, an actor's ability to circulate information to other actors depends on its position in the network, while its ability to be a source of social reinforcement depends on its level of clusterisation, also referred to as the density of neighborhoods, or, put differently, on how many of contacts are linked with oter members of the network (Namtirtha et al, 2021;Centola, 2010). The social network analysis (SNA), a technique devoted to study and investigate networks, uses indexes to quantify the network characteristics.…”