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Accurate ranking of influential spreaders in networks based on dynamically asymmetric link weights
2017
Physical review. E
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Results show that they generally outperform rankings based on the nodes' degree and k-shell index while maintaining a low computational complexity. ...
An s-shell decomposition scheme further assigns an s-shell index or weighted coreness to the nodes. ...
This will put the computational complexity at the same level as those based on the degree and k-shell decomposition. ...
doi:10.1103/physreve.96.022323
pmid:28950650
pmcid:PMC7217521
fatcat:wqjpqviltrfnvmzluzs2ibg3cy
Identify Influential Spreaders in Complex Networks Based on Potential Edge Weights
2016
International Journal of Innovative Computing, Information and Control
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In this paper, a novel method called evidential k-shell centrality based on potential edge weight is proposed to identify influential spreaders. ...
infected nodes in real complex networks. ...
In this paper, we propose a new approach to identify influential spreaders in complex network called evidential k-shell centrality based on potential edge weight. ...
doi:10.24507/ijicic.12.02.581
fatcat:z5dv4m27vrctbeayyazvya7alm
Identifying and Ranking Influential Nodes in Complex Networks Based on Dynamic Node Strength
2021
Algorithms
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In this paper, we propose a new ranking method, Dynamic Node Strength Decomposition, based on decomposing network. ...
Identifying and ranking the node influence in complex networks is an important issue. ...
Conclusions In this paper, we propose an efficient ranking method based on decomposing networks, Dynamic Node Strength Decomposition, to identify and rank the node influence in complex networks. ...
doi:10.3390/a14030082
doaj:ebe17918ecd246dca9257409f6f25ed7
fatcat:u2acyscksvd7boupby2qnet5ay
Weighted H-index for identifying influential spreaders
[article]
2017
arXiv
pre-print
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In this paper, a weighted h-index centrality based on virtual nodes extension is proposed to quantify the spreading influence of nodes in complex networks. ...
Simulation results on real-world networks reveal that the proposed method provides more accurate and more consistent ranking than the five classical methods. ...
[9] argued that the most influential spreaders are the nodes reside in the core of the network by the k-shell decomposition analysis. ...
arXiv:1710.05272v1
fatcat:ddhb34oowzaqlooicp4yecfpbq
Estimating Shell-Index in a Graph with Local Information
[article]
2018
arXiv
pre-print
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The k-shell decomposition method is a widely used method which assigns a shell-index value to each node based on its influential power. ...
For network scientists, it has always been an interesting problem to identify the influential nodes in a given network. ...
They defined the weighted degree that considers both the degree as well as the weights of the connected edges. Then, the weighted degree is used while applying the k-shell decomposition method. ...
arXiv:1805.10391v2
fatcat:ro4zwrhpxbhgrekzfhyvcqazra
Ranking Influential Nodes in Complex Networks with Information Entropy Method
2020
Complexity
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The ranking of influential nodes in networks is of great significance. ...
On the basis of the k-shell method, we propose an improved multiattribute k-shell method by using the iterative information in the decomposition process. ...
. is method uses node degree to rank the importance of nodes. e following details show the decomposition principle of the k-shell method. ...
doi:10.1155/2020/5903798
fatcat:uotc4wiouvcxnc42npsuqygun4
Centrality Measures in Complex Networks: A Survey
[article]
2020
arXiv
pre-print
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In complex networks, each node has some unique characteristics that define the importance of the node based on the given application-specific context. ...
Some of these centrality measures can be computed using local information of the node, such as degree centrality and semi-local centrality measure. ...
They define the weighted degree that considers both the degree as well as the weights of the connected edges. Then the weighted degree is used while applying the k-shell decomposition method. ...
arXiv:2011.07190v1
fatcat:obm6lgm6ojaw5iuk3pigvomoo4
A Bio-Inspired Methodology of Identifying Influential Nodes in Complex Networks
2013
PLoS ONE
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How to identify influential nodes is a key issue in complex networks. The degree centrality is simple, but is incapable to reflect the global characteristics of networks. ...
in weighted networks. ...
We are also grateful to Haixin Zhang, Yuxian Du and Daijun Wei for their comments on an earlier version of the paper and Yajuan Zhang for discussions and comparison of Physarum centrality in the revised ...
doi:10.1371/journal.pone.0066732
pmid:23799129
pmcid:PMC3682958
fatcat:arrj7hwafjeg7b47zwmuejgl4i
Spreading Information in Complex Networks: An Overview and Some Modified Methods
[chapter]
2018
Graph Theory - Advanced Algorithms and Applications
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Degree centrality, closeness centrality, betweenness centrality, k-core decomposition, mixed degree decomposition, improved k-shell decomposition, etc., are some of these methods. ...
Some systems are highly affected by a small fraction of influential nodes. Number of fast and efficient spreaders in a network is much less compared to the number of ordinary members. ...
Decomposition using k-shell iteration factor Very recently, Wang and Zhao put forward a method for fast ranking of influential nodes [17] in complex networks. ...
doi:10.5772/intechopen.69204
fatcat:wti6r3elvvbo3cq4xca3kvolcy
Influential Node Ranking in Complex Information Networks Using A Randomized Dynamics-Sensitive Approach
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2112.02927v1 fatcat:cvsxxm3qb5cizoyx5dchwgsema
From a theoretical standpoint, one can argue that a factor of the degree of nodes in the hyper-graph approximates influentiality. ...
Identifying the most influential nodes in information networks has been the focus of many research studies. ...
Output: A ranking of nodes in : based on their influentiality using the aggregated weights of their edges in : p . # Sampling -graphs 1: For q′ rounds: 2: Build a -graph J F by selecting ( edges each with ...
arXiv:2112.02927v2
fatcat:2r3frhlribdyra7z47fwlcxmi4
Weighted h-index for Identifying Influential Spreaders
2019
Symmetry
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Experimental results on twelve real networks reveal that s h was more accurate and more monotonic than h w and four previous measures in ranking the spreading influence of a node evaluated by the single ...
In this paper, we propose weighted h-index h w and h-index strength s h to measure spreading capability and identify the most influential spreaders. ...
However, coreness is a metric based on k-shell decomposition, which assigns many nodes to the same shell. The nodes in the same shell actually have different spreading abilities [19] . ...
doi:10.3390/sym11101263
fatcat:cb4hzwk45vdkzazn2a4lm7djfq
Influential Node Identification in Command and Control Networks Based on Integral k-Shell
2019
Wireless Communications and Mobile Computing
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This motivates us to propose a method based on an integral k-shell to identify the influential nodes in a command and control network. ...
This new method takes both the global and local information of nodes into account, introduces the historical k-shell and a 2-order neighboring degree, and refines the k-shell decomposition process in a ...
decomposition. e complexity of the k-shell decomposition algorithm is o(N). e complexity of the influential node-ranking algorithm based on the integral kshell is the sum of the complexities of the 2-order ...
doi:10.1155/2019/6528431
fatcat:ezhwzj6xnzgffpysptout7nw5i
Identifying influential spreaders in complex networks based on gravity formula
2016
Physica A: Statistical Mechanics and its Applications
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2016 pre-print arXiv:1505.02476v2 fatcat:ahnm4mqy6vfhvk3bhzdolhqhcmOther Versions
centrality index to identify the influential spreaders in complex networks. ...
that our method can effectively identify the influential spreaders in real networks as well as synthetic networks. ...
For example, by defining the combination of node's degree and node's strength as the weighted degree of a node in weighted networks, Garas et al have proposed a new k-shell decomposition method for weighted ...
doi:10.1016/j.physa.2015.12.162
fatcat:s2kgsgzqknhmxk4kwskrdb6at4
Identification of Influential Nodes via Effective Distance-based Centrality Mechanism in Complex Networks
2021
Complexity
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Efficient identification of influential nodes is one of the essential aspects in the field of complex networks, which has excellent theoretical and practical significance in the real world. ...
Therefore, to resolve these challenging issues, we propose a novel effective distance-based centrality (EDBC) algorithm for the identification of influential nodes in concerning networks. ...
In this study, we proposed an effective-based centrality method for detecting the influential nodes in complex networks. ...
doi:10.1155/2021/8403738
fatcat:4vtgv4u2a5a53btbsrueyiqhju
Identification of influential spreaders in complex networks using HybridRank algorithm
2018
Scientific Reports
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Identifying the influential spreaders in complex networks is crucial to understand who is responsible for the spreading processes and the influence maximization through networks. ...
In this paper, we propose the HybridRank algorithm using a new hybrid centrality measure for detecting a set of influential spreaders using the topological features of the network. ...
For the undirected networks, the ranked list (σ) of top-10 of network nodes obtained using the SIR process is compared with the HybridRank, eigenvector, degree and k-shell decomposition ranked lists. ...
doi:10.1038/s41598-018-30310-2
pmid:30093716
pmcid:PMC6085314
fatcat:pyy6ybvoefbbbcmn2p4mzrxfee
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