A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition

2021 ◽  
Vol 35 (24) ◽  
Author(s):  
Pengli Lu ◽  
Zhiru Zhang ◽  
Yuhong Guo ◽  
Yahong Chen
Keyword(s):  
Information Dissemination ◽  
Method Comparison ◽  
Practical Significance ◽  
Centrality Measures ◽  
Global Information ◽  
Weighted Degree ◽  
Influential Nodes ◽  
Potential Impact ◽  
Local Range ◽  
Global Influence

It has theoretical interest and practical significance to find out influential nodes which make the information spread faster and more extensive in complex networks. A variety of centrality measures have been proposed to identify influential nodes, while numerous of them are one-sided and may lead to inaccurate for identification. To overcome this issue, based on the defined minimum weighted degree decomposition, we propose a novel centrality method for identifying influential nodes by combining the local and global information. First, considering the local topological attribute of node and spread characteristic of neighbor nodes, the local influentiality is defined as the node’s influence in the local range. Then, a weighted neighborhood coreness centrality is presented as the node’s global influence capability by taking into account the potential impact of edges on information dissemination among nodes and position characteristic of node. Finally, taking the combinatorial centrality of local and global range as the final influence of node is more comprehensive and universally applicable. We use Susceptible–Infected–Recovered (SIR) model, monotonicity, Kendall’s tau correlation coefficient and imprecision function to estimate the performance of our method. Comparison experiments conducted on 14 real-world networks indicate the effectiveness of the proposed method.

scholarly journals Identification of Influential Nodes via Effective Distance-based Centrality Mechanism in Complex Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Aman Ullah ◽  
Bin wang ◽  
Jinfang Sheng ◽  
Jun Long ◽  
Nasrullah Khan
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Practical Significance ◽  
Centrality Measures ◽  
Sir Epidemic Model ◽  
Effective Distance ◽  
H Index ◽  
Sir Epidemic ◽  
Spreading Dynamics ◽  
Influential Nodes

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. A valuable number of approaches have been developed and deployed in these areas where just a few have used centrality measures along with their concerning deficiencies and limitations in their studies. 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. EDBC algorithm comprises factors such as the power of K-shell, degree nodes, effective distance, and numerous levels of neighbor’s influence or neighborhood potential. The performance of the proposed algorithm is evaluated on nine real-world networks, where a susceptible infected recovered (SIR) epidemic model is employed to examine the spreading dynamics of each node. Simulation results demonstrate that the proposed algorithm outperforms the existing techniques such as eigenvector, betweenness, closeness centralities, hyperlink-induced topic search, H-index, K-shell, page rank, profit leader, and gravity over a valuable margin.

Influential nodes in planar trusses and meshes using centrality measures

2021 ◽  
Author(s):  
P. Sangeetha ◽  
R. Sundareswaran ◽  
M. Shanmugapriya ◽  
S. Srinidhi ◽  
K. Sowmya
Keyword(s):  
Centrality Measures ◽  
Influential Nodes

Evaluation of invulnerability of scale-free networks using total information of local sub-graph

2018 ◽  
Vol 29 (08) ◽  
pp. 1850075
Author(s):  
Tingyuan Nie ◽  
Xinling Guo ◽  
Mengda Lin ◽  
Kun Zhao
Keyword(s):  
Mutual Information ◽  
Complex Network ◽  
Fundamental Problem ◽  
The Self ◽  
Practical Significance ◽  
Scale Free ◽  
Total Information ◽  
Scale Free Networks ◽  
Influential Nodes ◽  
Definition Of

The quantification for the invulnerability of complex network is a fundamental problem in which identifying influential nodes is of theoretical and practical significance. In this paper, we propose a novel definition of centrality named total information (TC) which derives from a local sub-graph being constructed by a node and its neighbors. The centrality is then defined as the sum of the self-information of the node and the mutual information of its neighbor nodes. We use the proposed centrality to identify the importance of nodes through the evaluation of the invulnerability of scale-free networks. It shows both the efficiency and the effectiveness of the proposed centrality are improved, compared with traditional centralities.

Improved influential nodes identification in complex networks

2021 ◽  
pp. 1-9
Author(s):  
Shi Dong ◽  
Wengang Zhou
Keyword(s):  
Theoretical Analysis ◽  
Complex Networks ◽  
Network Structure ◽  
Information Entropy ◽  
Network System ◽  
Weighted Degree ◽  
Identification Methods ◽  
Hybrid Mechanism ◽  
Influential Nodes ◽  
Influential Node

Influential node identification plays an important role in optimizing network structure. Many measures and identification methods are proposed for this purpose. However, the current network system is more complex, the existing methods are difficult to deal with these networks. In this paper, several basic measures are introduced and discussed and we propose an improved influential nodes identification method that adopts the hybrid mechanism of information entropy and weighted degree of edge to improve the accuracy of identification (Hm-shell). Our proposed method is evaluated by comparing with nine algorithms in nine datasets. Theoretical analysis and experimental results on real datasets show that our method outperforms other methods on performance.

Information Dissemination Mechanism Based on Cloud Computing Cross-Media Public Opinion Network Environment

2021 ◽  
Vol 14 (2) ◽  
pp. 70-83
Author(s):  
Ping Liu
Keyword(s):  
Cloud Computing ◽  
Public Opinion ◽  
Computer Technology ◽  
Information Dissemination ◽  
Transmission Mechanism ◽  
Practical Significance ◽  
Propagation Mechanism ◽  
Cross Media ◽  
User Density ◽  
Network Public Opinion

As an important expression of social public opinion, network public opinion develops rapidly with the popularization of the internet and then affects the real society. Therefore, the use of computer technology to study the network public opinion information transmission mechanism has strong practical significance. The purpose of this paper is to use cloud computing to realize the research of information dissemination mechanism in the context of cross-media public opinion network. Researched from three aspects of operator supervision, number of media, and user density, the hotspot propagation mechanism of Storm platform given in this paper can solve the efficiency problems of traditional algorithms while ensuring accuracy, improve efficiency, and lay the foundation for the research on the monitoring of Internet public opinion propagation.

A dynamic weighted TOPSIS method for identifying influential nodes in complex networks

2018 ◽  
Vol 32 (19) ◽  
pp. 1850216 ◽  
Author(s):  
Pingle Yang ◽  
Xin Liu ◽  
Guiqiong Xu
Keyword(s):  
Complex Networks ◽  
Centrality Measures ◽  
Topsis Method ◽  
Decision Making Problem ◽  
Significant Research ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Influential Nodes ◽  
Influential Node ◽  
Grey Relational

Identifying the influential nodes in complex networks is a challenging and significant research topic. Though various centrality measures of complex networks have been developed for addressing the problem, they all have some disadvantages and limitations. To make use of the advantages of different centrality measures, one can regard influential node identification as a multi-attribute decision-making problem. In this paper, a dynamic weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is developed. The key idea is to assign the appropriate weight to each attribute dynamically, based on the grey relational analysis method and the Susceptible–Infected–Recovered (SIR) model. The effectiveness of the proposed method is demonstrated by applications to three actual networks, which indicates that our method has better performance than single indicator methods and the original weighted TOPSIS method.

scholarly journals Influential Performance of Nodes Identified by Relative Entropy in Dynamic Networks

2020 ◽  
Vol 08 (01) ◽  
pp. 93-112
Author(s):  
Péter Marjai ◽  
Attila Kiss
Keyword(s):  
Diffusion Process ◽  
Complex Networks ◽  
Relative Entropy ◽  
Information Diffusion ◽  
Dynamic Networks ◽  
Centrality Measures ◽  
Topsis Method ◽  
Cover Time ◽  
Influential Nodes ◽  
Different Characteristics

For decades, centrality has been one of the most studied concepts in the case of complex networks. It addresses the problem of identification of the most influential nodes in the network. Despite the large number of the proposed methods for measuring centrality, each method takes different characteristics of the networks into account while identifying the “vital” nodes, and for the same reason, each has its advantages and drawbacks. To resolve this problem, the TOPSIS method combined with relative entropy can be used. Several of the already existing centrality measures have been developed to be effective in the case of static networks, however, there is an ever-increasing interest to determine crucial nodes in dynamic networks. In this paper, we are investigating the performance of a new method that identifies influential nodes based on relative entropy, in the case of dynamic networks. To classify the effectiveness, the Suspected-Infected model is used as an information diffusion process. We are investigating the average infection capacity of ranked nodes, the Time-Constrained Coverage as well as the Cover Time.

scholarly journals Transformation of the Civil Right to the Freedom of Expression in the Internet

2018 ◽  
Vol 4 ◽  
pp. 43-47
Author(s):  
Ksenia A. Ivanova ◽  
Keyword(s):  
Information Exchange ◽  
System Analysis ◽  
Freedom Of Expression ◽  
Legal Regulation ◽  
Practical Significance ◽  
Scientific Article ◽  
Global Information ◽  
Scientific Methods ◽  
Analysis And Synthesis ◽  
The Right

Purpose. The purpose of the scientific article is to study the modern information society, as well as to consider the conditions for the development of global information and communication networks, the global information exchange system. The author has studied the current legal regulation of freedom of speech to achieve this goal. Methodology. The article applies general scientific methods of system analysis and synthesis, as well as private scientific methods: comparative, sociological. The use of methods of analysis and synthesis will determine the key scientific concepts for research. In addition, an institutional research method will be used. On its basis, in particular, the originality of the forms of regulation of the right to freedom of opinion has been revealed; specificity of regulation of restrictions of this right. The article concludes that the existing regulation does not correspond to the level of development of public relations. The fact that there are no legal instruments that can prevent the falsification of information in the media indicates that there are problems in ensuring the right of citizens to freedom of expression in cyberspace, which ensures the relevance of the study. Scientific and practical significance. Within the framework of the research, a complex scientific theoretical and legal analysis of the constitutional and legal category “the right of citizens to freedom of opinion” in cyberspace was carried out; a comparison of Russian and foreign legislation. Results. It was suggested that the concept of the right to freedom of opinion in cyberspace be structured into separate elements. Following the logic of the proposed classification, the author proposes the main directions of improving the legal regulation of this right. The significance of the study is made by proposals to improve Russian legislation in the sphere of securing the right of citizens to freedom of opinion, as well as further development of mechanisms for the realization of this right in cyberspace.

scholarly journals Spheres of Legislation: Polarization and Most Influential Nodes in Behavioral Context

2020 ◽  
Author(s):  
Andrew C. Phillips ◽  
Mohammad T. Irfan ◽  
Luca Ostertag-Hill
Keyword(s):  
Network Structure ◽  
Clustering Algorithms ◽  
Generative Models ◽  
Machine Learning Techniques ◽  
Centrality Measures ◽  
Behavioral Context ◽  
Real World Data ◽  
Game Theoretic ◽  
Influential Nodes ◽  
Structural Centrality

Abstract Game-theoretic models of influence in networks often assume the network structure to be static. In this paper, we allow the network structure to vary according to the underlying behavioral context. This leads to several interesting questions on two fronts. First, how do we identify different contexts and learn the corresponding network structures using real-world data? We focus on the U.S. Senate and apply unsupervised machine learning techniques, such as fuzzy clustering algorithms and generative models, to identify spheres of legislation as context and learn an influence network for each sphere. Second, how do we analyze these networks in order to gain an insight into the role played by the spheres of legislation in various interesting constructs like polarization and most influential nodes? To this end, we apply both game-theoretic and social network analysis techniques. In particular, we show that game-theoretic notion of most influential nodes brings out the strategic aspects of interactions like bipartisan grouping, which structural centrality measures fail to capture.

scholarly journals СТВОРЕННЯ БАНКІВСЬКИХ КЛАСТЕРІВ ДЛЯ ПІДВИЩЕННЯ ІННОВАЦІЙНОСТІ БАНКІВСЬКОЇ СИСТЕМИ УКРАЇНИ

2019 ◽  
pp. 56-65
Author(s):  
М. С. Татар ◽  
Ю. А. Нужнова ◽  
О. О. Косяк
Keyword(s):  
Cluster Analysis ◽  
Method Comparison ◽  
Banking System ◽  
Developed Countries ◽  
Comparison Method ◽  
Practical Significance ◽  
Innovation Cluster ◽  
Innovative Cluster ◽  
New Ideas ◽  
Sustainable Economic Growth

Formulation of the problem. Today most developed countries associate long-term sustainable economic growth with the transition to innovative path of development, so the problem of creating and ensuring the efficient functioning of innovative cluster structures, in particular banking, is extremely urgent. The aim of the research is systematization of theoretical and methodological provisions on the creation of banking cluster structures to enhance the innovativeness of Ukraine banking system. The subject of the research is formation and functioning of innovative banking clusters in Ukraine. The methods of the research: meaningful method, comparison method, induction and deduction methods, cluster analysis, etc. The hypothesis of the research. There is a need to create innovative banking clusters to increase the innovativeness of the Ukraine banking system. The statement of basic materials. The definitions of the term “innovation cluster” and “banking innovations” are analyzed. It is determined that banking innovations in Ukraine are aimed mainly at creating new or modernizing existing banking products and services and developing automated banking systems. The advantages of creation of innovative banking clusters are characterized and algorithm of banks cluster analysis realization and algorithm of innovative banking clusters creation are developed. The originality and practical significance of the research are algorithm of banks cluster analysis realization and algorithm of innovative banking clusters creation, which makes possible to determine the sequence of actions required for cluster structures formation. Conclusions and perspectives of further research. Prospects of creation of innovative banking clusters are characterized and algorithm of banks cluster analysis realization and algorithm of innovative banking clusters creation are developed. These algorithms will ensure close interaction between the cluster members and the generation of new ideas, will increase the innovativeness of the production and providing of banking services.

Sign in / Sign up

Export Citation Format

Share Document