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Influencer identification of dynamical networks based on an information entropy dimension reduction method
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作者 段东立 纪思源 袁紫薇 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第4期375-384,共10页
Identifying critical nodes or sets in large-scale networks is a fundamental scientific problem and one of the key research directions in the fields of data mining and network science when implementing network attacks,... Identifying critical nodes or sets in large-scale networks is a fundamental scientific problem and one of the key research directions in the fields of data mining and network science when implementing network attacks, defense, repair and control.Traditional methods usually begin from the centrality, node location or the impact on the largest connected component after node destruction, mainly based on the network structure.However, these algorithms do not consider network state changes.We applied a model that combines a random connectivity matrix and minimal low-dimensional structures to represent network connectivity.By using mean field theory and information entropy to calculate node activity,we calculated the overlap between the random parts and fixed low-dimensional parts to quantify the influence of node impact on network state changes and ranked them by importance.We applied this algorithm and the proposed importance algorithm to the overall analysis and stratified analysis of the C.elegans neural network.We observed a change in the critical entropy of the network state and by utilizing the proposed method we can calculate the nodes that indirectly affect muscle cells through neural layers. 展开更多
关键词 dynamical networks network influencer low-dimensional dynamics network disintegration
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The Research on Social Networks Public Opinion Propagation Influence Models and Its Controllability 被引量:9
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作者 Lejun Zhang Tong Wang +3 位作者 Zilong Jin Nan Su Chunhui Zhao Yongjun He 《China Communications》 SCIE CSCD 2018年第7期98-110,共13页
Public opinion propagation control is one of the hot topics in contemporary social network research. With the rapid dissemination of information over the Internet, the traditional isolation and vaccination strategies ... Public opinion propagation control is one of the hot topics in contemporary social network research. With the rapid dissemination of information over the Internet, the traditional isolation and vaccination strategies can no longer achieve satisfactory results. A positive guidance technology for public opinion diffusion is urgently needed. First, based on the analysis of influence network controllability and public opinion diffusion, a positive guidance technology is proposed and a new model that supports external control is established. Second, in combination with the influence network, a public opinion propagation influence network model is designed and a public opinion control point selection algorithm(POCDNSA) is proposed. Finally, An experiment verified that this algorithm can lead to users receiving the correct guidance quickly and accurately, reducing the impact of false public opinion information; the effect of CELF is no better than that of the POCDNSA algorithm. The main reason is that the former is completely based on the diffusion cascade information contained in the training data, but does not consider the specific situation of the network structure and the diffusion of public opinion information in the closed set. thus, the effectiveness and feasibility of the algorithm is proven. The findings of this article therefore provide useful insights for the implementation of public opinion control. 展开更多
关键词 social network public opinion propagation control influence network
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Network-based structure optimization method of the anti-aircraft system 被引量:2
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作者 ZHAO Qingsong DING Junyi +2 位作者 LI Jichao LI Huachao XIA Boyuan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第2期374-395,共22页
The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The con... The anti-aircraft system plays an irreplaceable role in modern combat. An anti-aircraft system consists of various types of functional entities interacting to destroy the hostile aircraft moving in high speed. The connecting structure of combat entities in it is of great importance for supporting the normal process of the system. In this paper, we explore the optimizing strategy of the structure of the anti-aircraft network by establishing extra communication channels between the combat entities.Firstly, the thought of combat network model(CNM) is borrowed to model the anti-aircraft system as a heterogeneous network. Secondly, the optimization objectives are determined as the survivability and the accuracy of the system. To specify these objectives, the information chain and accuracy chain are constructed based on CNM. The causal strength(CAST) logic and influence network(IN) are introduced to illustrate the establishment of the accuracy chain. Thirdly, the optimization constraints are discussed and set in three aspects: time, connection feasibility and budget. The time constraint network(TCN) is introduced to construct the timing chain and help to detect the timing consistency. Then, the process of the multi-objective optimization of the structure of the anti-aircraft system is designed.Finally, a simulation is conducted to prove the effectiveness and feasibility of the proposed method. Non-dominated sorting based genetic algorithm-Ⅱ(NSGA2) is used to solve the multiobjective optimization problem and two other algorithms including non-dominated sorting based genetic algorithm-Ⅲ(NSGA3)and strength Pareto evolutionary algorithm-Ⅱ(SPEA2) are employed as comparisons. The deciders and system builders can make the anti-aircraft system improved in the survivability and accuracy in the combat reality. 展开更多
关键词 anti-aircraft system optimization combat network model(CNM) causal strength(CAST)logic influence network(IN) time constraint network(TCN)
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Network-Based Synthesis Evaluation Model
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作者 Cheng shi 《International Journal of Technology Management》 2014年第1期52-53,共2页
With the explosion of information, people are receiving numerous of messages at any moment. How to explore the relationships between everything you know? And how to make wise decisions while stuck in a huge informati... With the explosion of information, people are receiving numerous of messages at any moment. How to explore the relationships between everything you know? And how to make wise decisions while stuck in a huge information net? 展开更多
关键词 information influence network
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Recommending Personalized POIs from Location Based Social Network
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作者 Haiying Che Di Sang Billy Zimba 《Journal of Beijing Institute of Technology》 EI CAS 2018年第1期137-145,共9页
Location based social networks( LBSNs) provide location specific data generated from smart phone into online social networks thus people can share their points of interest( POIs). POI collections are complex and c... Location based social networks( LBSNs) provide location specific data generated from smart phone into online social networks thus people can share their points of interest( POIs). POI collections are complex and can be influenced by various factors,such as user preferences,social relationships and geographical influence. Therefore,recommending new locations in LBSNs requires to take all these factors into consideration. However,one problem is how to determine optimal weights of influencing factors in an algorithm in which these factors are combined. The user similarity can be obtained from the user check-in data,or from the user friend information,or based on the different geographical influences on each user's check-in activities. In this paper,we propose an algorithm that calculates the user similarity based on check-in records and social relationships,using a proposed weighting function to adjust the weights of these two kinds of similarities based on the geographical distance between users. In addition,a non-parametric density estimation method is applied to predict the unique geographical influence on each user by getting the density probability plot of the distance between every pair of user's check-in locations. Experimental results,using foursquare datasets,have shown that comparisons between the proposed algorithm and the other five baseline recommendation algorithms in LBSNs demonstrate that our proposed algorithm is superior in accuracy and recall,furthermore solving the sparsity problem. 展开更多
关键词 location based social network personalized geographical influence location recommendation non-parametric probability estimates
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ComRank: Joint Weight Technique for the Identification of Influential Communities 被引量:1
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作者 Muhammad Azam Zia Zhongbao Zhang +2 位作者 Ximing Li Haseeb Ahmad Sen Su 《China Communications》 SCIE CSCD 2017年第4期101-110,共10页
Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people... Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people. However, there is little work to shed light on how to rank communities while considering their levels that are determined by the quality of their published contents. In this paper, we propose solution for measuring the influence of communities and ranking them by considering joint weight composed of internal and external influence of communities. To address this issue, we design a novel algorithm called Com Rank: a modification of Page Rank, which considers the joint weight in order to identify impact of each community and ranking them. We use real-world data trace in citation network and perform extensive experiments to evaluate our proposed algorithm. The comparative results depict significant improvements by our algorithm in community ranking due to the inclusion of proposed weighting feature. 展开更多
关键词 online social networks community rank citation network Page Rank influence
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Mathematical Models of Self-Appraisal in Social Networks
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作者 ANDERSON Brian D.O. YE Mengbin 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2021年第5期1604-1633,共30页
In social networks where individuals discuss opinions on a sequence of topics,the selfconfidence an individual exercises in relation to one topic,as measured by the weighting given to their own opinion as against the ... In social networks where individuals discuss opinions on a sequence of topics,the selfconfidence an individual exercises in relation to one topic,as measured by the weighting given to their own opinion as against the opinion of all others,can vary in the light of the self-appraisal by the individual of their contribution to the previous topic.This observation gives rise to a type of model termed a De Groot-Friedkin model.This paper reviews a number of results concerning this model.These include the asymptotic behavior of the self-confidence(as the number of topics goes to infinity),the possible emergence of an autocrat or small cohort of leaders,the effect of changes in the weighting given to opinions of others(in the light for example of their perceived expertise in relation to a particular topic under discussion),and the inclusion in the model of individual behavioral characteristics such as humility,arrogance,etc.Such behavioral characteristics create new opportunities for autocrats to emerge. 展开更多
关键词 De Groot Degroot-Friedkin opinion dynamics SELF-APPRAISAL social influence network
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