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Social Network information propagation Model Based on Individual Behavior

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China Communications 2017年第7期14卷 78-92页

作者： Lejun Zhang Hongjie Li Chunhui Zhao Xiaoying Lei College of information Engineering Yangzhou University College of Computer Science and Technology Harbin Engineering University

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.

关键词： social network information propagation individual behavior propagation delay

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Impact of Online Community Structure on information propagation:Empirical Analysis and Modeling

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Journal of Harbin Institute of Technology(New Series) 2013年第3期20卷 124-128页

作者： Zhong He Lian-Ren Wu Xia Chen Ting-Jie Lu School of Economics and Management Beijing University of Post and Telecommunications

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.

关键词： community structure information propagation user behavior heterogeneity

维普期刊数据库

Influence of double layer network coupling mode on information propagation speed

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Influence of double layer network coupling mode on informati...

Modeling multi-type information propagation based on multi-layer networks

第30届中国控制与决策会议

作者： Fan Ke-Da Jiang Guo-Ping Nanjing University of Posts and Telecommunications College of automation

Facing the problem of information propagation in double layer network, some structural parameters based on the double layer network, which affecting information propagation are proposed: node degree, clustering and the interlayer connections. Introduce the construction of double layer network, propose a new propagation model of double layer network. According to different influencing factors, simulate the propagation process of information on different coupling mode networks. Research shows that different coupling modes have various influences on the speed of information propagation in double layer network.

关键词： information propagation coupling mode double layer network

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Modeling multi-type information propagation based on multi-l...

Understanding the mechanism of social tie in the propagation process of social network with communication channel

第40届中国控制会议

作者： Libin Chen Yuan Feng Chengyi Zeng Hongfu Liu Jing Chen College of Intelligence Science and Technology National University of Defense Technology Taiyuan Satellite Launch Center

information propagation in the real world is a complex system interacting in a multi-dimensional space. information propagation networks are diverse and coupled, and existing research cannot meet the needs of actual interaction situations. The multi-layer complex network model provides a suitable framework to model multiple types of information propagation. Previous research on information propagation networks focused on single-layer networks. However, in the real world, different types of information propagation will affect each other, and the network structure of each type of information is different. In this article, we have established a multi-layer complex network model for multi-type information propagation. We first considered the transfer and interaction process of various types of information on the multilayer network, and modeled and analyzed its topology and dynamic behavior. In addition, we provide a multi-layer network model framework. It can reflect the key attributes of network information transmission capabilities. Based on the micro-Markov chain method, we analyzed and deduced the information propagation threshold and balance point of the network, and obtained the influence of each parameter in the model on the information propagation process of each layer of the network. Our work proves that deleting nodes or edges in the network will increase the information propagation threshold of the multi-layer networks, and then provide a method to weaken the ability of multi-type information propagation on the network.

关键词： multi-layer complex network information propagation multi-type information

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Frontiers of Computer Science 2019年第6期13卷 1296-1308页

作者： Kai LI Guangyi LV Zhefeng WANG Qi LIU Enhong CHEN Lisheng QIAO Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of ChinaHefei 230027China

The propagation of information in online social networks plays a critical role in modern life,and thus has been studied *** have proposed a series of propagation models,generally,which use a single transition probability or consider factors such as content and time to describe the way how a user activates her/his ***,the research on the mechanism how social ties between users play roles in propagation process is still ***,comprehensive summary of factors which affect user’s decision whether to share neighbor’s content was lacked in existing works,so that the existing models failed to clearly describe the process a user be activated by a *** this end,in this paper,we analyze the close correspondence between social tie in propagation process and communication channel,thus we propose to exploit the communication channel to describe the information propagation process between users,and design a social tie channel(STC)*** model can naturally incorporate many factors affecting the information propagation through edges such as content topic and user preference,and thus can effectively capture the user behavior and relationship characteristics which indicate the property of a social *** experiments conducted on two real-world datasets demonstrate the effectiveness of our model on content sharing prediction between users.

关键词： information propagation social networks mechanism of social tie communication channel

Influence maximization with limit cost in social network

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Science China(information Sciences) 2013年第7期56卷 168-181页

作者： WANG Yue HUANG WeiJing ZONG Lang WANG TengJiao YANG DongQing Department of Computer Science School of Information Central University of Finance and Economics Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of Education

Social networking service (SNS) applications are changing the way information spreads in online communities. As real social relationships are projected into SNS applications, word of mouth has been an important factor in the information spreading processes of those applications. By assuming each user needs a cost to accept some specific information, this paper studies the initial "seed user" selection strategy to maximize information spreading in a social network with a cost budget. The main contributions of this paper are: 1) proposing a graphic SEIR model (gSEIR) by extending the epidemic compartmental model to simulate the dynamic information spreading process between individuals in the social network; 2) proposing a formal definition for the influence maximization problem with limit cost (IMLC) in social networks, and proving that this problem can be transformed to the weighted set-cover problem (WSCP) and thus is NP-Complete; 3) providing four different greedy algorithms to solve the IMLC problem; 4) proposing a heuristic algorithm based on the method of Lagrange multipliers (HILR) for the same problem; 5) providing two parts of experiments to test the proposed models and algorithms in this paper. In the first part, we verify that gSEIR can generate similar macro-behavior as an SIR model for the information spreading process in an online community by combining the micro-behaviors of all the users in that community, and that gSEIR can also simulate the dynamic change process of the statuses of all the individuals in the corresponding social networks during the information spreading process. In the second part, by applying the simulation result from gSEIR as the prediction of information spreading in the given social network, we test the effectiveness and efficiency of all provided algorithms to solve the influence maximization problem with cost limit. The result show that the heuristic algorithm HILR is the best for the IMLC problem.

关键词： data mining social network influence maximization graph-based diffusion model information propagation