基于强关系的移动社交网络信息传播机理建模与仿真研究
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摘要
【目的/意义】随着微信的广泛应用,移动社交网络结构正逐渐由弱关系连接向强关系连接转变。研究强关系结构下的移动社交网络信息传播机理有助于建立有效的管理机制。【方法/过程】通过引入强关系结构的特征变量,构建SEIRC模型,并采用Matlab软件对模型进行模拟仿真。【结果/结论】结果表明,在基于强关系的移动社交网络中,用户关系强度、传播转化率以及潜伏转化率与信息传播速率成正比;免疫系数与传播速率成反比;易传播者评论系数、免疫者评论系数的增加能够降低免疫节点数量,提高信息传播效率。
【Purpose/significance】With the popular use of WeChat, mobile social network structure is turning from weak ties to strong ties. Exploring information dissemination mechanism in strong ties structure contributes to the effective information management for mobile social network.【Method/process】The SEIRC model is constructed by introducing variables related to strong ties,and Matlab software is employed to simulate the model.【Result/conclusion】The result shows that user relationship strength, disseminator converted rate and lurker converting rate are in direct proportion to information diffusion speed; the coefficient of immune is inversely proportional to diffusion speed; the higher coefficient of active disseminators' and immunes' comments can lead to the fewer immune nodes, which may increases the efficiency of information spreading.
【Purpose/significance】With the popular use of WeChat, mobile social network structure is turning from weak ties to strong ties. Exploring information dissemination mechanism in strong ties structure contributes to the effective information management for mobile social network.【Method/process】The SEIRC model is constructed by introducing variables related to strong ties,and Matlab software is employed to simulate the model.【Result/conclusion】The result shows that user relationship strength, disseminator converted rate and lurker converting rate are in direct proportion to information diffusion speed; the coefficient of immune is inversely proportional to diffusion speed; the higher coefficient of active disseminators' and immunes' comments can lead to the fewer immune nodes, which may increases the efficiency of information spreading.
引文
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21王宏波.微信朋友圈信息传播:演化模型构建与仿真[J].现代情报,2017,37(9):81-85.
22 Sudbury A.The Proportion of the Population Never Hearing a Rumour[J].Journal of Applied Probability,1985,22(2):443-446.
23毛艳.基于创新扩散理论的微信信息传播[D].上海:上海工程技术大学,2015.
2陈海涛,宋姗姗,李健佳.创业生态系统的信息传播机制及路径研究[J].情报理论与实践,2017,40(9):101-104.
3尹熙成,朱恒民,魏静.在线社交网络中具有传播价值的弱关系识别研究[J].情报杂志,2016,35(3):125-130.
4崔金栋,郑鹊,孙硕.基于改良SEIR模型的微博话题式信息传播研究[J].情报科学,2017,35(12):22-27.
5 Granovetter M S.The Strength of Weak Ties[J].The American Journal of Sociology,1973,78(6):1360-1380.
6 Shi Z,Rui H,Whinston A B.Content sharing in a social broadcasting environment:evidence from Twitter.MIS Q[J].Mis Quarterly,2014,38(1):123-142.
7 Keeling M J,Eames K T.Networks and epidemic models[J].Journal of the Royal Society Interface,2005,2(4):295-307.
8 Kermack W,Mckendrick A.Contributions to the Mathematical Theory of Epidemics[EB/OL].http://rspa.royalsocietypublishing.org/content/138/834/55.full.pdf,2013-11-25.
9朱海涛,赵捧未,秦春秀.一种改进的移动社交网络SEIR信息传播模型研究[J].情报科学,2016,36(3):92-97.
10 Zhao L,Wang J,Chen Y.SIHR rumor spreading model in social networks[J].Physica A Statistical Mechanics and Its Applications,2012,391(7):2444-2453.
11 Liu D,Chen X.Rumor Propagation in Online Social Networks Like Twitter-A Simulation Study[C]//Third International Conference on Multimedia Information NET-WORKING and Security.IEEE,2011:278-282.
12 WANG,Yiping,FENG.ReTweeting Analysis and Prediction in Microblogs:An Epidemic Inspired Approach[J].China Communications,2013,10(3):13-24.
13 Xu R,Li H,Xing C.Research on Information Dissemination Model for Social Networking Services[J].International Journal of Computer Science and Application,2013,2(1):1-6.
14 Wang R,Chen B W,Chen B W,et al.Modeling of largescale social network services based on mechanisms of information diffusion:Sina Weibo as a case study[J].Future Generation Computer Systems,2017,74(C):291-301.
15 Wu M,Guo J,Zhang C.Social Media Communication Model Research Bases on Sina-weibo[M].Berlin:Springer Berlin Heidelberg,2011:445-454.
16 Li J,Dong T,Li M.Research of Social Network Information Propagation Model Based on Public Interest and Opinion[J].Social Networking,2016,5(2):75-81.
17孙晓娥,边燕杰.吸引海归:弱关系比强关系更具优势?[N].中国社会科学报,2011-06-28(011).
18冯娇,姚忠.基于强弱关系理论的社会化商务购买意愿影响因素研究[J].管理评论,2015,27(12):99-109.
19 Liu D,Wang W,Li H.Evolutionary Mechanism and Information Supervision of Public Opinions in Internet Emergency[J].Procedia Computer Science,2013,(17):973-980.
20 Witbooi P J.Stability of an SEIR epidemic model with independent stochastic perturbations[J].Physica A Statistical Mechanics and its Applications,2013,392(20):4928-4936.
21王宏波.微信朋友圈信息传播:演化模型构建与仿真[J].现代情报,2017,37(9):81-85.
22 Sudbury A.The Proportion of the Population Never Hearing a Rumour[J].Journal of Applied Probability,1985,22(2):443-446.
23毛艳.基于创新扩散理论的微信信息传播[D].上海:上海工程技术大学,2015.
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