Web 2.0时代,建模和预测在线信息流行度是信息传播中的重要问题.本文基于社交网络系统信息传播的机制,通过假设和简化,提出了分支过程的概率模型,来描述在线社交网络信息的流行度动力学过程.对典型在线社交网络系统的信息流行度数据和...Web 2.0时代,建模和预测在线信息流行度是信息传播中的重要问题.本文基于社交网络系统信息传播的机制,通过假设和简化,提出了分支过程的概率模型,来描述在线社交网络信息的流行度动力学过程.对典型在线社交网络系统的信息流行度数据和网络结构数据进行了分析,统计结果表明信息流行度衰减遵循幂律分布(幂指数为1.8),微博网络的入度和出度分布也均服从幂律分布(幂指数为1.5).模型仿真结果发现,该模型能够再现真实社交网络数据的若干特征,且信息流行度与网络结构相关.对模型方程进行求解得到理论预测的结果与仿真分析和实际数据结果相符合.展开更多
Predicting and modeling of items popularity on web 2.0 have attracted great attention of many scholars. From the perspective of information competition, we propose a probabilistic model using the branching process to ...Predicting and modeling of items popularity on web 2.0 have attracted great attention of many scholars. From the perspective of information competition, we propose a probabilistic model using the branching process to characterize the process in which micro-blogging gains its popularity. The model is analytically tractable and can reproduce several characteristics of empirical micro-blogging data on Sina micro-blog, the most popular micro- blogging system in China. We find that the information competition on micro-blog network leads to the decay of information popularity obeying power law distribution with exponent about 1.5, and the value is similar to the exponent of degree distribution of micro-blog network. Furthermore, the mean popularity is decided by the probability of innovating a new message. Our work presents evidence supporting the idea that two distinct factors affect information popularity： information competition and social network structure.展开更多
In this paper,we study the dynamic evolution of friendship network in SNS(Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has wi...In this paper,we study the dynamic evolution of friendship network in SNS(Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community,but also on the friendship network generated by those friends.In addition,we propose a model which is based on two processes:first,connecting nearest neighbors;second,strength driven attachment mechanism.The model reflects two facts:first,in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor;second,new nodes connect more likely to nodes which have larger weights and interactions,a phenomenon called strength driven attachment(also called weight driven attachment).From the simulation results,we find that degree distribution P(k),strength distribution P(s),and degree-strength correlation are all consistent with empirical data.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 71601005 and 71231002the National Basic Research Program of China under Grant No 2013CB329604
文摘Predicting and modeling of items popularity on web 2.0 have attracted great attention of many scholars. From the perspective of information competition, we propose a probabilistic model using the branching process to characterize the process in which micro-blogging gains its popularity. The model is analytically tractable and can reproduce several characteristics of empirical micro-blogging data on Sina micro-blog, the most popular micro- blogging system in China. We find that the information competition on micro-blog network leads to the decay of information popularity obeying power law distribution with exponent about 1.5, and the value is similar to the exponent of degree distribution of micro-blog network. Furthermore, the mean popularity is decided by the probability of innovating a new message. Our work presents evidence supporting the idea that two distinct factors affect information popularity： information competition and social network structure.
基金Supported by Program for New Centurty Excellent Talents in University under Grant No. NCET-11-0597the Fundamental Research Funds for the Central Universities under Grant No. 2012RC1002
文摘In this paper,we study the dynamic evolution of friendship network in SNS(Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community,but also on the friendship network generated by those friends.In addition,we propose a model which is based on two processes:first,connecting nearest neighbors;second,strength driven attachment mechanism.The model reflects two facts:first,in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor;second,new nodes connect more likely to nodes which have larger weights and interactions,a phenomenon called strength driven attachment(also called weight driven attachment).From the simulation results,we find that degree distribution P(k),strength distribution P(s),and degree-strength correlation are all consistent with empirical data.
