In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behav...In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.展开更多
E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of ...E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of Enron dataset and the distribution of node degree and strength are analyzed. Then, some rules of e-mail communication network evolution are found. Second, the model of e-mail information propagation is described, and e-mail communication network evolution model based on user information propagation is proposed. Lastly, the simulation proves the correctness of the distribution characteristic of degree and strength of the model proposed and then verifies that the model proposed is closer to the real situation of e-mail communication network through parameter comparison. This research provides the basis for other researches on social network evolution and data communication.展开更多
Online social networking sites ( OSNS) ,as a popular social media platform,have been developed massively for business and research purposes. In this paper,it investigated the impact of community structure in online so...Online social networking sites ( OSNS) ,as a popular social media platform,have been developed massively for business and research purposes. In this paper,it investigated the impact of community structure in online social network on information propagation. A SI (Susceptible-Infected) model based on community structure was proposed. In the SI model,the heterogeneity of user's active time was taken into account. From the results,it was found that the number of links among communities determines the fraction of infected nodes. With the increase of the number of groups G,however,the fraction of infected nodes remains approximately constant. The simulation results will be of great significance: the information will last relatively short for group networks which have either a small or a large number of groups. The results can be useful for optimizing or controlling information,such as propagating rumors in online social networks.展开更多
The rapid development of the Internet has broadened the channels of dissemination of information,it has also led to the rapid and widespread propagation of rumors,which can have a serious negative impact socially.In t...The rapid development of the Internet has broadened the channels of dissemination of information,it has also led to the rapid and widespread propagation of rumors,which can have a serious negative impact socially.In this paper,an improved ISR-WV rumor propagation model integrating multichannels is proposed by considering the system’s time delay,and the influence of different channels of propagation on the dynamic process is further analyzed.Moreover,the basic reproduction number R0,rumor-free equilibrium,and rumor-prevailing equilibrium,as well as their stability,are deduced.Then,an optimal control problem with pulse vaccination is designed.Finally,the validity of the model and theoretical results is verified by numerical simulations and a practical application.The results show that the rumor propagation threshold R0 is more sensitive to the rate of the propagation of the information base channel.The shorter the thinking timeτ_(1)required for the ignorant to react after obtaining the information,the larger the final scale of propagation.Under this condition,the time delayτ_(2)spent by a spreader in producing a video is negatively related to the final scale of the propagation;conversely,a longerτ_(1)implies that the person tends to more cognizant,which can suppress the spread of rumors.Under this condition,τ_(2)has little effect on the final scale of propagation.In addition,the results also prove that timely implementation of the pulse vaccination control strategy of popular science education can effectively control the propagation of rumors and reduce their negative impact.展开更多
User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influenc...User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influence on the information multi-step communication in a micro-biog. The multi-steps of information communication are divided into first-step and non-first-step, and user influence is classified into five dimensions. Actual data from the Sina micro-blog is collected to construct the model by means of an approach based on structural equations that uses the Partial Least Squares （PLS） technique. Our experimental results indicate that the dimensions of the number of fans and their authority significantly impact the information of first-step conxrnunication. Leader rank has a positive impact on both first-step and non-first-step communication. Moreover, global centrality and weight of friends are positively related to the information non-first-step communication, but authority is found to have much less relation to it.展开更多
This paper analyzes the selfish-mine strategy in the Bitcoin blockchain introduced in 2013 by I.Eyal and E.G.Sirer.This strategy could be used by a colluding pool of miners to earn more than their fair share of the mi...This paper analyzes the selfish-mine strategy in the Bitcoin blockchain introduced in 2013 by I.Eyal and E.G.Sirer.This strategy could be used by a colluding pool of miners to earn more than their fair share of the mining revenue and in consequence to force other honest miners to join them to decrease the variance of their revenues and make their monthly revenues more predictable.It is a very dangerous dynamic that could allow the rogue pool of miners to go toward a majority by accumulating powers of news adherents and control the entire network.Considering that the propagation delay of information between any two miners in the network,which is not negligible and follows a normal distribution with mean proportional to the physical distance between the two miners,and a constant variance independent of others'delays,we prove that no guarantee can be given about the success or failure of the selfish-mine attack because of the variability of information propagation in the network.展开更多
In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get...In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.展开更多
In this letter, an integrated application of the prediction for radio wave propagation with the Geographic Information System (GIS) is presented and a real prediction system based on GIS is implemented.
In the applications of water regime monitoring, incompleteness, and inaccuracy of sensor data may directly affect the reliability of acquired monitoring information. Based on the spatial and temporal correlation of wa...In the applications of water regime monitoring, incompleteness, and inaccuracy of sensor data may directly affect the reliability of acquired monitoring information. Based on the spatial and temporal correlation of water regime monitoring information, this paper addresses this issue and proposes an information fusion method to implement data rectification. An improved Back Propagation (BP) neural network is used to perform data fusion on the hardware platform of a stantion unit, which takes Field-Programmable Gate Array (FPGA) as the core component. In order to verify the effectiveness, five measurements including water level, discharge and velocity are selected from three different points in a water regime monitoring station. The simulation results show that this method can recitify random errors as well as gross errors significantly.展开更多
基金sponsored by the National Natural Science Foundation of China under grant number No. 61100008 the Natural Science Foundation of Heilongjiang Province of China under Grant No. LC2016024
文摘In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.
基金sponsored by the National Natural Science Foundation of China under grant number No. 61100008, 61201084the China Postdoctoral Science Foundation under Grant No. 2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund (Postdoctoral Youth Talent Program) under Grant No. LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No. LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No. QC2015076Funds for the Central Universities of China under grant number HEUCF100602
文摘E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of Enron dataset and the distribution of node degree and strength are analyzed. Then, some rules of e-mail communication network evolution are found. Second, the model of e-mail information propagation is described, and e-mail communication network evolution model based on user information propagation is proposed. Lastly, the simulation proves the correctness of the distribution characteristic of degree and strength of the model proposed and then verifies that the model proposed is closer to the real situation of e-mail communication network through parameter comparison. This research provides the basis for other researches on social network evolution and data communication.
基金Sponsored by the National Basic Research Program of China (973 Program) (Grant No. 2012CB315805)National Natural Science Foundation ofChina (Grant No. 71172135)
文摘Online social networking sites ( OSNS) ,as a popular social media platform,have been developed massively for business and research purposes. In this paper,it investigated the impact of community structure in online social network on information propagation. A SI (Susceptible-Infected) model based on community structure was proposed. In the SI model,the heterogeneity of user's active time was taken into account. From the results,it was found that the number of links among communities determines the fraction of infected nodes. With the increase of the number of groups G,however,the fraction of infected nodes remains approximately constant. The simulation results will be of great significance: the information will last relatively short for group networks which have either a small or a large number of groups. The results can be useful for optimizing or controlling information,such as propagating rumors in online social networks.
基金This work was partially supported by the Project for the National Natural Science Foundation of China(Grant Nos.72174121 and 71774111)the Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning,and the Project for the Natural Science Foundation of Shanghai(Grant No.21ZR1444100).
文摘The rapid development of the Internet has broadened the channels of dissemination of information,it has also led to the rapid and widespread propagation of rumors,which can have a serious negative impact socially.In this paper,an improved ISR-WV rumor propagation model integrating multichannels is proposed by considering the system’s time delay,and the influence of different channels of propagation on the dynamic process is further analyzed.Moreover,the basic reproduction number R0,rumor-free equilibrium,and rumor-prevailing equilibrium,as well as their stability,are deduced.Then,an optimal control problem with pulse vaccination is designed.Finally,the validity of the model and theoretical results is verified by numerical simulations and a practical application.The results show that the rumor propagation threshold R0 is more sensitive to the rate of the propagation of the information base channel.The shorter the thinking timeτ_(1)required for the ignorant to react after obtaining the information,the larger the final scale of propagation.Under this condition,the time delayτ_(2)spent by a spreader in producing a video is negatively related to the final scale of the propagation;conversely,a longerτ_(1)implies that the person tends to more cognizant,which can suppress the spread of rumors.Under this condition,τ_(2)has little effect on the final scale of propagation.In addition,the results also prove that timely implementation of the pulse vaccination control strategy of popular science education can effectively control the propagation of rumors and reduce their negative impact.
基金supported by the National Natural Science Foundation of China(Grant No.60873246)China Information Technology Security Evaluation Center
文摘User influence is generally considered as one of the most critical factors that affect information cascading spreading. Based on this common assumption, this paper proposes a theoretical model to examine user influence on the information multi-step communication in a micro-biog. The multi-steps of information communication are divided into first-step and non-first-step, and user influence is classified into five dimensions. Actual data from the Sina micro-blog is collected to construct the model by means of an approach based on structural equations that uses the Partial Least Squares （PLS） technique. Our experimental results indicate that the dimensions of the number of fans and their authority significantly impact the information of first-step conxrnunication. Leader rank has a positive impact on both first-step and non-first-step communication. Moreover, global centrality and weight of friends are positively related to the information non-first-step communication, but authority is found to have much less relation to it.
基金Author of this article,M.BA,would like to thank the laboratory MODAL’X of Universite Paris Nanterre to support this work。
文摘This paper analyzes the selfish-mine strategy in the Bitcoin blockchain introduced in 2013 by I.Eyal and E.G.Sirer.This strategy could be used by a colluding pool of miners to earn more than their fair share of the mining revenue and in consequence to force other honest miners to join them to decrease the variance of their revenues and make their monthly revenues more predictable.It is a very dangerous dynamic that could allow the rogue pool of miners to go toward a majority by accumulating powers of news adherents and control the entire network.Considering that the propagation delay of information between any two miners in the network,which is not negligible and follows a normal distribution with mean proportional to the physical distance between the two miners,and a constant variance independent of others'delays,we prove that no guarantee can be given about the success or failure of the selfish-mine attack because of the variability of information propagation in the network.
基金supported by the National Natural Science Foundation of China(No.92167202,61925102,U21B2014,62101069)the National Key R&D Program of China(No.2020YFB1805002)。
文摘In order to support the future digital society,sixth generation(6G)network faces the challenge to work efficiently and flexibly in a wider range of scenarios.The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline,which obviously leads to a 6G network lacking of adaptation to dynamic environments.Recently,with the aid of sensing enhancement,more environment information can be obtained.Based on this,from radio wave propagation perspective,we propose a predictive 6G network with environment sensing enhancement,the electromagnetic wave propagation characteristics prediction enabled network(EWave Net),to further release the potential of 6G.To this end,a prediction plane is created to sense,predict and utilize the physical environment information in EWave Net to realize the electromagnetic wave propagation characteristics prediction timely.A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWave Net.Several promising application cases of EWave Net are analyzed and the open issues to achieve this goal are addressed finally.
文摘In this letter, an integrated application of the prediction for radio wave propagation with the Geographic Information System (GIS) is presented and a real prediction system based on GIS is implemented.
基金Supported by the National Natural Science Foundation of China (No. 60774092, No. 60901003)the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20070294027)
文摘In the applications of water regime monitoring, incompleteness, and inaccuracy of sensor data may directly affect the reliability of acquired monitoring information. Based on the spatial and temporal correlation of water regime monitoring information, this paper addresses this issue and proposes an information fusion method to implement data rectification. An improved Back Propagation (BP) neural network is used to perform data fusion on the hardware platform of a stantion unit, which takes Field-Programmable Gate Array (FPGA) as the core component. In order to verify the effectiveness, five measurements including water level, discharge and velocity are selected from three different points in a water regime monitoring station. The simulation results show that this method can recitify random errors as well as gross errors significantly.
