广西师范大学学报(自然科学版) ›› 2016, Vol. 34 ›› Issue (3): 14-24.doi: 10.16088/j.issn.1001-6600.2016.03.003

• • 上一篇    下一篇

加权网络上的多信息传播研究

陈德霞, 邹艳丽, 王意, 李可, 黄李   

  1. 广西师范大学电子工程学院,广西多源信息挖掘与安全重点实验室,广西桂林541004
  • 收稿日期:2016-03-25 出版日期:2016-09-30 发布日期:2018-09-17
  • 通讯作者: 邹艳丽(1972—),女,河北沧州人,广西师范大学教授,博士。E-mail: eeyzou@gxnu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(11562003);广西多源信息挖掘与安全重点实验室系统性研究课题基金(13-A-02-03);广西研究生教育创新计划项目资助课题(YCSZ2014098)

Multi-information Dissemination on Weighted Network

CHEN Dexia, ZOU Yanli, WANG Yi, LI Ke, HUANG Li   

  1. Guangxi Key Lab of Multi-source Information Mining and Security,College of Electronic Engineering,Guangxi Normal University,Guilin Guangxi 541004,China
  • Received:2016-03-25 Online:2016-09-30 Published:2018-09-17

摘要: 分别在GBBV加权网络和实际数据集上研究了2条信息的传播特性。假定2条信息的传播率相同,信息自身的吸引力不同,其中信息1的吸引力高,信息2的吸引力低,通过实验发现:在网络平均度为6~8时最不利于处于低吸引力信息2的传播;当网络平均度小于8时,信息2的传播范围随着网络平均边权值的增大而增加。本文提出几种增加低吸引力信息2的初始传播源提升其传播范围的方法,并对这几种方法的效果进行比较,结果发现在稀疏网络中,按大度节点降序增加初始传播源的方法,效果更加显著,只需增加少量初始传播源就可使信息2的传播范围超过信息1。

关键词: 加权网络, 信息传播, 网络平均度

Abstract: The propagation characteristics of the two pieces of information are studied respectively on the GBBV weighted network and a real data set. Assuming that the spread rates of the two pieces of information are the same,the attractiveness of the information itself is different from each other,in which the attractiveness of information 1 is relative high,and the attractiveness of information 2 is relative low,study shows that when the average degree of a network is 6 to 8,the spread range of the low attractiveness information 2 is relative small. When the average degree of the network is less than 8,the spread range of the information 2 increases with the increase of the average weight of the network. This paper puts forward several methods to improve the propagation range of information 2 by increasing the number of its initial propagation source,and then compares the results of these methods. It is found that the effect of increasing the initial propagation nodes by descending degree is notable in sparse networks,and the propagation range of information 2 will exceed information 1 by only adding a small amount of initial propagation nodes.

Key words: weighted networks, information dissemination, average degree

中图分类号: 

  • TM711
[1] ZHAO L,WANG J,CHEN Y,et al. SIHR rumor spreading model in social networks[J]. Physica A: Statistical Mechanics and Its Applications,2012,391(7): 2444-2453.
[2] LÜ L,CHEN D B,ZHOU T. The small world yields the most effective information spreading[J]. New Journal of Physics,2011,13(12): 123005.
[3] BETTENCOURT L M A,CINTRÓN-ARIAS A,KAISER D I,et al. The power of a good idea: quantitative modeling of the spread of ideas from epidemiological models[J]. Physica A: Statistical Mechanics and Its Applications,2006,364: 513-536.
[4] 邵峰晶,孙仁诚,李淑静. 一种具有抑制作用的多信息传播模型[J]. 复杂系统与复杂性科学,2010,7(1): 47-51.
[5] WU Weiwei. The cooperation-competition model for the hot topics of Chinese microblogs[J]. Applied Mechanics and Materials,2013,380:2724-2727.
[6] SAHNEH F D,SCOGLIO C. Competitive epidemic spreading over arbitrary multilayer networks[J]. Physical Review E,2014,89(6): 062817.
[7] LIU Zhenzhen, WANG Xingyuan, WANG Maoji. Competition between two kinds of information among random-walking individuals[J]. Chinese Physics B,2012,21(4): 048902.
[8] AHN Y Y,JEONG H,MASUDA N,et al. Epidemic dynamics of two species of interacting particles on scale-free networks[J]. Physical Review E,2006,74: 066113.
[9] TRPEVSKI D,TANG W K S,KOCAREV L. Model for rumor spreading over networks[J]. Physical Review E,2010,81(5): 056102.
[10] BARRAT A,BARTHÉLEMY M,VESPIGNANI A. Weighted evolving networks: coupling topology and weight dynamics[J]. Physical Review Letters,2004,92(22): 228701.
[11] 潘灶烽,汪小帆. 一种可大范围调节聚类系数的加权无标度网络模型[J]. 物理学报,2006,55(8): 4058-4064.
[12] YANG Chanxia,TANG Minxuan,TANG Haiqiang,et al. Local-world and cluster-growing weighted networks with controllable clustering[J]. International Journal of Modern Physics C,2014,25(5): 522-526.
[13] 谢斐,张昊,陈超. 无标度网络中边权重对传播的影响[J]. 计算机应用研究,2013,30(1): 238-240.
[14] ZHAO L,WANG X,QIU X,et al. A model for the spread of rumors in Barrat-Barthelemy-Vespignani (BBV) networks[J]. Physica A: Statistical Mechanics and Its Applications,2013,392(21): 5542-5551.
[15] GANG Y,TAO Z,JIE W,et al. Epidemic spread in weighted scale-free networks[J]. Chinese Physics Letters,2005,22(2): 510.
[16] 曾柳娟. 基于加权网络模型的谣言传播与防控的研究[D]. 桂林: 广西师范大学,2012.
[17] 胡如北,蒋国平,宋波.加权网络中改进的熟人免疫策略研究[J]. 计算机工程,2016,42(8):91-95,100.
[18] TRPEVSKI D,STAMENOV K,KOCAREV L. Modeling information spreading on complex networks[J]. Contributions, Sec Math Tech Sci, 2012, 33(1/2):23-45.
[1] 王 意,邹艳丽,李 可,黄 李. 分布式电站入网方式对电网同步的影响[J]. 广西师范大学学报(自然科学版), 2017, 35(4): 24-31.
[2] 黄李, 邹艳丽, 王意, 李可. 分布式电站的3种入网方式比较研究[J]. 广西师范大学学报(自然科学版), 2017, 35(3): 30-36.
[3] 谢蓉,邹艳丽,傅杰. 基于动力学的电网发电机故障恢复策略研究[J]. 广西师范大学学报(自然科学版), 2017, 35(1): 1-6.
[4] 傅杰,邹艳丽,谢蓉. 簇网络的同步及稳定性研究[J]. 广西师范大学学报(自然科学版), 2017, 35(1): 7-15.
[5] 梁宏, 童张法, 周立亚, 沈星灿, 潘英明. 基于广西大学生化学实验技能竞赛对应用型人才培养的思考[J]. 广西师范大学学报(自然科学版), 2016, 34(3): 116-120.
[6] 郑京, 邹艳丽, 何郁郁, 陈德霞. 两种分布式电站连接策略对网络动态特性的影响[J]. 广西师范大学学报(自然科学版), 2015, 33(2): 15-21.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 广西师范大学学报(自然科学版)编辑部
地址:广西桂林市三里店育才路15号 邮编:541004
电话:0773-5857325 E-mail: gxsdzkb@mailbox.gxnu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发