Please wait a minute...
文章检索
复杂系统与复杂性科学  2022, Vol. 19 Issue (3): 14-19    DOI: 10.13306/j.1672-3813.2022.03.002
  本期目录 | 过刊浏览 | 高级检索 |
协同对社会传播的影响
卢炯, 许新建
上海大学数学系,上海 200444
SynergisticEffects in Social Contagions on Networks
LU Jiong, XU Xinjian
Department of Mathematics, Shanghai University, Shanghai 200444, China
全文: PDF(1764 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 协同是复杂网络上的传播过程的普遍现象,鉴于已有研究主要聚焦于连续模型,关于离散模型的研究相对较少,研究了两态(活跃或者怠惰)阈值模型,利用母函数方法重点考察了怠惰态个体之间协同对传播结果以及系统鲁棒性的影响。与不考虑协同相比,正的协同作用会促进传播,从而降低系统的鲁棒性;反之,负的协同作用会抑制传播,从而提高系统的鲁棒性。与均匀网络相比,非均匀网络上的传播受到协同的影响更大。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
卢炯
许新建
关键词 社会传播阈值模型协同鲁棒性    
Abstract:Synergy is ubiquitous in contagion processes on complex networks. Most existing studies have been focused on the continuous models, yet the discrete models received less attention. Motivated by this, we employ the generating function method to study a two-state (active or inactive) threshold model on complex networks with different synergistic effects. Compared to the case without synergy, the positive synergy enhances prevalence and weakens systematic robustness. The negative synergy, however, plays an opposite role. These effects are strengthened when the network is heterogeneous.
Key wordssocial contagion    threshold model    synergy    robustness
收稿日期: 2021-05-07      出版日期: 2022-10-12
ZTFLH:  O231.5  
基金资助:国家自然科学基金(12071281)
通讯作者: 许新建(1978-),男,江苏连云港人,博士,教授,主要研究方向为复杂网络。   
作者简介: 卢炯(1996-),男,上海人,硕士研究生,主要研究方向为复杂网络。
引用本文:   
卢炯, 许新建. 协同对社会传播的影响[J]. 复杂系统与复杂性科学, 2022, 19(3): 14-19.
LU Jiong, XU Xinjian. SynergisticEffects in Social Contagions on Networks. Complex Systems and Complexity Science, 2022, 19(3): 14-19.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2022.03.002      或      https://fzkx.qdu.edu.cn/CN/Y2022/V19/I3/14
[1] 李翔, 刘宗华, 汪秉宏. 网络传播动力学[J]. 复杂系统与复杂性科学, 2010, 7(2/3): 33-37.
LI X, LIU Z H, WANG B H. On spreading dynamics on networks[J]. Complex Systems and Complexity Science, 2010, 7(2/3): 33-37.
[2] PORTER M A, GLEESON J P. Dynamical Systems on Networks: a Tutorial[M]. Switzerland:Springer, 2016.
[3] KEELING M J, ROHANI P. Modeling Infectious Diseases in Humans and Animals[M]. Princeton :Princeton University Press, 2007.
[4] AHMED E, AGIZA H N. On modeling epidemics including latency, incubation and variable susceptibility[J]. Physica A, 1998, 253(1-4): 347-352.
[5] TAYLOR H M, KARLIN S. An Introduction to Stochastic Modeling[M]. Burlington: Academic Press, 1984.
[6] 刘宗华, 阮中远, 唐明. 复杂网络上的流行病传播[M]. 北京: 高等教育出版社, 2021.
[7] GÓMEZ S, ARENAS, A, BORGE-HOLTHOEFER J, et al. Discrete-time Markov chain approach to contact-based disease spreading in complex networks[J]. EPL, 2010, 89(3): 38009.
[8] WATTS D J. A simple model of global cascades on complex networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2002, 99(9): 5766-5771.
[9] SCHELLING T C. Hockey helmets, concealed weapons, and daylight saving[J]. Journal of Conflict Resolution, 1973, 17(3): 381-428.
[10] 李小林, 许润杰, 娄洁等. 双层网络上的社会传播[J]. 复杂系统与复杂性科学, 2019, 16(4): 13-18.
LI X L, XU R J, LOU J, et al. Social contagions on duplex networks[J]. Complex Systems and Complexity Science, 2019, 16(4): 13-18.
[11] GRANOVETTER M. Threshold models of collective behavior[J]. American Journal of Sociology, 1978, 83(6): 1420-1443.
[12] MORRIS S. Contagion[J]. Review of Economic Studies, 2000, 67: 57-78.
[13] GLEESON J P. Cascades on correlated and modular random networks[J]. Physical Review E, 2008, 77(4): 046117.
[14] COUPECHOUX E, LELARGE M. How clustering affects epidemics in random networks[J]. Advances in Applied Probability, 2014, 46: 985-1008.
[15] BACKLUND V P, SARAMÄKI J, PAN R K. Effects of temporal correlations on cascades[J]. Physical Review E, 2014, 89(6): 062815.
[16] 李小林, 袁梦, 王鹏等. 复杂网络中权重对舆情传播的影响[J]. 应用数学与计算数学学报, 2018, 32: 588-597
LI X L, YUAN M, WANG P, et al. Impact of weights on opinion propagation in complex networks[J]. Communication on Applied Mathematics and Computation, 2018, 32: 588-597.
[17] MCCULLEN N, RUCKLIDGE A, BALE C, et al. Multiparameter models of innovation diffusion on complex networks[J]. SIAM Journal on Applied Dynamical Systems, 2013, 12(1): 515-532.
[18] MELNIK S, WARD J A, GLEESON J P, et al. Multi-stage complex contagions[J]. Chaos, 2013, 23(1): 013124.
[19] WANG W, TANG M, ZHANG H F, et al. Dynamics of social contagions with memory of nonredundant information[J]. Physical Review E, 2015, 92(1): 012820.
[20] RUAN Z, IÑGUEZ G, KARSAI M, et al. Kinetics of social contagion[J]. Physical Review Letters, 2015, 115(21): 218702.
[21] PÉREZ-RECHE F J, LUDLAM J J, TARASKIN S N, et al. Synergy in spreading processes: from exploitative to explorative foraging strategies[J]. Physical Review Letters, 2011, 106(21): 218701.
[22] BRODWE-RODGERS D, PÉREZ-RECHE F J, TARASKIN S N. Effects of local and global network connectivity on synergistic epidemics[J]. Physical Review E, 2015, 92(6): 062814.
[23] GÓMEZ-GARDEÑES J, LOTERO L, TARASKIN S N, et al. Explosive contagion in networks[J]. Scientific Reports, 2016, 6(1):19767.
[24] LIU Q H, WANG W, TANG M, et al. Explosive spreading on complex networks: the role of synergy[J]. Physical Review E, 2017, 95(4): 042320.
[25] TARASKIN S N, PÉREZ-RECHE F J. Bifurcations in synergistic epidemics on random regular graphs[J]. Journal of Physics A: Mathematical and Theoretical, 2019, 52(19): 195101.
[26] OGURA M, MEI W, SUGIMOTO K. Synergistic effects in networked epidemic spreading dynamics[J]. IEEE Transactions on Circuits and Systems II, 2020, 67(3): 496-500.
[27] JUUL J S, PORTER M A. Synergistic effects in threshold models on networks[J]. Chaos, 2018, 28(1): 013115.
[28] ERDÖS P, RÉNYI A. On random graphs[J]. Publicationes Mathematicae Debrecen, 1959, 6: 290-297.
[29] CATANZARO M, BOGUÑÁ M, PASTOR-SATORRAS R. Generation of uncorrelated random scale-free networks[J]. Physical Review E, 2005, 71(2): 027103.
[30] ALBERT R, JEONG H, BARABÁSI A L. Error and attack tolerance of complex networks[J]. Nature, 2000, 406(6794): 378-382.
[31] DO Y S, BAEK S K, ZHU C P, et al. Phase transition in a coevolving network of conformist and contrarian voters[J]. Physical Review E, 2013, 87(1): 012806.
[32] YANG H X, HUANG L. Opinion percolation in structured population[J]. Computer Physics Communications, 2015, 192: 124-129.
[1] 谭桂敏, 汪丽娜, 臧臣瑞. 耦合二分网络识别通信系统流量的时空特征[J]. 复杂系统与复杂性科学, 2022, 19(2): 71-79.
[2] 王丹丹, 菅利荣, 付帅帅. 战略性新兴产业集群生态链协同运作研究[J]. 复杂系统与复杂性科学, 2022, 19(1): 60-66.
[3] 翁克瑞, 沈卉, 侯俊东. 确定性社会影响力竞争扩散问题研究[J]. 复杂系统与复杂性科学, 2021, 18(4): 21-29.
[4] 徐云程, 胡华, 孙小军. 三层无标度关联网络协同传播模型阈值研究[J]. 复杂系统与复杂性科学, 2021, 18(3): 1-8.
[5] 王哲, 李建华, 康东, 冉淏丹. 复杂网络鲁棒性增强策略研究综述[J]. 复杂系统与复杂性科学, 2020, 17(3): 1-26.
[6] 覃炳发, 李科赞. 桂林市公交换乘网络的实证分析[J]. 复杂系统与复杂性科学, 2020, 17(2): 22-30.
[7] 李小林, 许润杰, 娄洁, 许新建. 双层网络上的社会传播[J]. 复杂系统与复杂性科学, 2019, 16(4): 13-18.
[8] 肖琴, 罗帆. 基于复杂网络的两栖水上飞机起降安全风险演化[J]. 复杂系统与复杂性科学, 2019, 16(2): 19-30.
[9] 宋甲秀, 杨晓翠, 张曦煌. 融合邻域鲁棒性及度均衡性的集体影响中心性[J]. 复杂系统与复杂性科学, 2019, 16(1): 26-35.
[10] 吴凌杰, 邹艳丽, 王瑞瑞, 姚飞, 汪洋. 电力信息相互依存网络与单层电网的级联故障比较[J]. 复杂系统与复杂性科学, 2018, 15(3): 11-18.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed