基于元胞自动机的人际信息传播模型研究
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摘要
人际信息传播既是建立人际关系和其他社会关系的必要手段,也是社会成员实现信息交流的重要渠道之一。在实现社会协作,传承社会文化,传递组织知识等方面,人际信息传播起着重要的作用。
由于社会是一个开放的系统,人是较为复杂的个体,使得人际信息传播的过程呈现复杂的现象。元胞自动机作为复杂系统研究的一种重要方法,逐步被用于社会科学的研究。因此,利用元胞自动机的方法对人际信息传播进行仿真研究具有重要的意义。
本文基于人际网络和元胞自动机原理,通过建立元胞自动机的人际信息传播模型,通过对人际信息传播模型进行仿真实验,研究传播意愿分布和信任度分布对信息的平均传播速度的影响,并分析信息的瞬时传播速度和信息共享水平之间的关系。在人际网络结构下,分别保持信任度分布均匀,传播意愿分别为正态、均匀、二项分布的情况,以及传播意愿分布均匀,信任度分别在正态、均匀、二项分布的情况下进行的仿真实验结果表明:在信任度均匀分布的情况下,传播意愿均值与信息的平均传播速度成近似正比关系;且平均传播速度随着传播意愿方差的增大而增大;在传播意愿均匀分布的情况下,信任度均值与信息的平均传播速度成近似正比关系;且平均传播速度随着信任度方差的增大而减小;信息的瞬时传播速度随网络中信息共享水平的增大而减小,当信息共享水平达到饱和时,瞬时传播速度为0。人际传播速度受人际网络的影响较大。
Personal communication is not only a necessary mean which is composed of human relation and other social relation. But also one of the important channel about achieving intercommunation of information in society. It plays an important role of social collaboration and inheriting of social culture. Personal dissemination of information operate important function on spreading the knowledge.
Society is a complex and huge system and the relation between people is complex, so the process of personal communication shows complexity. Cellular automata are often used for the study of social science as an important mode gradually. So it is important to study the process of personal communication.
In this paper, a model on personal dissemination of information based on cellular automata is introduced,based on theory of the personal network and cellular automata. Simulation are also conducted with the emulational experiment in order to investigate influence of different distribution of dissemination will and credibility on average speed of dissemination,and to analyse the relation between instantaneous speed of dissemination and information sharing in a group. Emulational experiment is performed in the condition of personal network, credibility being uniform distribution while will of dissemination alternate being normal school,uniform distribution and binormial distribution.and will of dissemination being uniform distribution while credibility alternate being normal school,uniform distribution and binormial distribution. It is shown that the will of dissemination and the average speed of dissemination are almost positive correlation,and average speed of dissemination is largening with the variance of will of dissemination diminishing while the credibility is uniform distribution. It is also shown that the credibility and the average speed of dissemination are almost positive correlation,and average speed of dissemination is largening with the variance of credibility largening while the will of dissemination is uniform distribution.There is negative correlation between information sharing and the instantaneous speed. When information sharing reach saturation, the instantaneous speed information diffusion is 0. The speed of personal dissemination influenced biggishly by the personal network.
由于社会是一个开放的系统,人是较为复杂的个体,使得人际信息传播的过程呈现复杂的现象。元胞自动机作为复杂系统研究的一种重要方法,逐步被用于社会科学的研究。因此,利用元胞自动机的方法对人际信息传播进行仿真研究具有重要的意义。
本文基于人际网络和元胞自动机原理,通过建立元胞自动机的人际信息传播模型,通过对人际信息传播模型进行仿真实验,研究传播意愿分布和信任度分布对信息的平均传播速度的影响,并分析信息的瞬时传播速度和信息共享水平之间的关系。在人际网络结构下,分别保持信任度分布均匀,传播意愿分别为正态、均匀、二项分布的情况,以及传播意愿分布均匀,信任度分别在正态、均匀、二项分布的情况下进行的仿真实验结果表明:在信任度均匀分布的情况下,传播意愿均值与信息的平均传播速度成近似正比关系;且平均传播速度随着传播意愿方差的增大而增大;在传播意愿均匀分布的情况下,信任度均值与信息的平均传播速度成近似正比关系;且平均传播速度随着信任度方差的增大而减小;信息的瞬时传播速度随网络中信息共享水平的增大而减小,当信息共享水平达到饱和时,瞬时传播速度为0。人际传播速度受人际网络的影响较大。
Personal communication is not only a necessary mean which is composed of human relation and other social relation. But also one of the important channel about achieving intercommunation of information in society. It plays an important role of social collaboration and inheriting of social culture. Personal dissemination of information operate important function on spreading the knowledge.
Society is a complex and huge system and the relation between people is complex, so the process of personal communication shows complexity. Cellular automata are often used for the study of social science as an important mode gradually. So it is important to study the process of personal communication.
In this paper, a model on personal dissemination of information based on cellular automata is introduced,based on theory of the personal network and cellular automata. Simulation are also conducted with the emulational experiment in order to investigate influence of different distribution of dissemination will and credibility on average speed of dissemination,and to analyse the relation between instantaneous speed of dissemination and information sharing in a group. Emulational experiment is performed in the condition of personal network, credibility being uniform distribution while will of dissemination alternate being normal school,uniform distribution and binormial distribution.and will of dissemination being uniform distribution while credibility alternate being normal school,uniform distribution and binormial distribution. It is shown that the will of dissemination and the average speed of dissemination are almost positive correlation,and average speed of dissemination is largening with the variance of will of dissemination diminishing while the credibility is uniform distribution. It is also shown that the credibility and the average speed of dissemination are almost positive correlation,and average speed of dissemination is largening with the variance of credibility largening while the will of dissemination is uniform distribution.There is negative correlation between information sharing and the instantaneous speed. When information sharing reach saturation, the instantaneous speed information diffusion is 0. The speed of personal dissemination influenced biggishly by the personal network.
引文
[1]卢山冰,黄孟芳.传播学理论百年回眸[J].西北大学学报, 2004.34(3):154-159.
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[12]来向红,王文平.基于元胞自动机的知识型组织中知识传播过程仿真研究[J].管理学报, 2006.3(5):514-518.
[13]唐泳,马永开.小世界社会网络中的信息传播(英文)[J].系统仿真学报, 2006.18(4):1084-1087.
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[16] Anderson, P. Complexity theory and organization science[J]. Organization Science, 10: 216-232.
[17] Giddens, A..Modernity and self-identity: Self and society in the late modern age[J]. Stanford, CA: Stanford University Press.
[18]方锦清,汪小帆,刘曾荣.略论复杂性问题和非线性复杂网络系统的研究[N].科技导报, 2004,22(2): 9 -12.
[19] Castells, M.. The rise of the network society (Vol.l.Theinformation age: Economy, society and culture) [J]. Oxford, UK: Blackwell Publishers.
[20] Meyers L A, Pourbohloul, Newman M E J, et al. Network theory and SARS: predicting outbreak diversity[J]. Journal of Theoretical Biology, 2005, 232:71-81.
[21] Keeling M J, Eames K T D. Networks and epidemic models[J]. Journal of the royal society interface,2005, 2 (4): 295-307.
[22] Pastor-Satorras R, Vespignani A. Immunization of complex networks[J]. Physical Review E, 2002,65:036104.
[23] Dezso Z, Barabasi A-L. Halting viruses in scale-free networks[J]. Physical Review E, 2002,65:055103(R).
[24] Cohen R, ben-Avraham D, Havlin S. Efficient Immunization Strategies for Computer Networks and Populations[J]. Physical Review Letters, 2003, 91:247901.
[25] Duan W-Q, Chen Z, Liu Z-R, et al. Efficient target strategies for contagion in scale-free networks[J]. Physical Review E, 2005, 72:026133.
[26] Zanette D H. Dynamics of rumor propagation on small-world networks[J]. Physical Review E, 2002,65:041908.
[27] Moreno Y, NekoveeM, Pacheco A F. Dynamics of rumor dissemination in complex networks[J]. Physical Review E, 2007, 69:066130.
[28] Barabasi A-L, Bonabeau E. Scale-Free Networks[J]. Scientific American, 2003, 288: 60-69.
[29] Niloy Ganguly, Biplab K Sikdar,Andreas Deutsch ,Geoffrey Canright ,P Pal Chaudhuri .A Survey on Cellular Automata[Z].
[30] WolframS. Statistica mechanics of cellular automata. http://stephenwolfram.com/publications articles/ca/83-statistical/, 2001.
[31]于乃功,阮晓钢.细胞自动机及其在复杂系统研究中的应用[J].计算机工程与应用, 2004.(12):25-28.
[32] Michael D Santoro,ShanthiGopalakrishnan.The institutionalization of knowledgetransfer activities within industry-university collaborative ventures[J].Journal of Engineering and Technology Management,2000,17:299-319.
[33]丹尼斯·麦奎尔,斯文·温德尔.祝建华,武伟译.大众传播模式论[M].上海译文出版社,1987.
[34]艾森伯格,古多尔.组织传播一平衡创造性和约束[M].北京:北京广播学院出版社,2004.
[2]许文惠,张成福.危机状态下的政府管理[M].北京:中国人民大学出版社, 1998.
[3]史安斌.危机传播与新闻发布[N].广州:南方日报出版社, 2004.
[4] li Farazmand. Handbook of Crisis and Emergency Management[J]. New York: Marcel Dekker,2001.
[5] William L.Waugh.Living with Hazards Dealing with Disasters: An Introduction toEmergency Management[J]. New York: M. E. Sharpe, Inc, 2000.
[6] Benoit, William L. Accounts and Apologies: A Theory of Image Restrotation Strategies[J]. Albany: SUNYPress, 1995.
[7] Darrell Birgitta.Crisis Communication Handbook[J]. Stockholm: SEMA, 2003.
[8]吴青峰.用元胞自动机研究舆论传播的复杂性[D].广西师范大学硕士论文, 2005.4.
[9]杨公成,付永.试论霍曼斯的人际传播理论[J].东南传播, 2006(5):39-40.
[10]薛可,余明阳.人际传播学[M].上海:同济大学出版社.2007.
[11]吴青峰,孔令江,刘慕仁.元胞自动机舆论传播模型中人员个性的影响[J].广西师范大学学报(自然科学版), 2004.22(4):5-8.
[12]来向红,王文平.基于元胞自动机的知识型组织中知识传播过程仿真研究[J].管理学报, 2006.3(5):514-518.
[13]唐泳,马永开.小世界社会网络中的信息传播(英文)[J].系统仿真学报, 2006.18(4):1084-1087.
[14]吴金闪,狄增如.从统计物理学看复杂网络研究.物理学进展[J]. 2004,24(1):19-46.
[15]王小云,邓科,赵鹤平.复杂网络研究进展[J].哲学研究, 2004(8).58-70.
[16] Anderson, P. Complexity theory and organization science[J]. Organization Science, 10: 216-232.
[17] Giddens, A..Modernity and self-identity: Self and society in the late modern age[J]. Stanford, CA: Stanford University Press.
[18]方锦清,汪小帆,刘曾荣.略论复杂性问题和非线性复杂网络系统的研究[N].科技导报, 2004,22(2): 9 -12.
[19] Castells, M.. The rise of the network society (Vol.l.Theinformation age: Economy, society and culture) [J]. Oxford, UK: Blackwell Publishers.
[20] Meyers L A, Pourbohloul, Newman M E J, et al. Network theory and SARS: predicting outbreak diversity[J]. Journal of Theoretical Biology, 2005, 232:71-81.
[21] Keeling M J, Eames K T D. Networks and epidemic models[J]. Journal of the royal society interface,2005, 2 (4): 295-307.
[22] Pastor-Satorras R, Vespignani A. Immunization of complex networks[J]. Physical Review E, 2002,65:036104.
[23] Dezso Z, Barabasi A-L. Halting viruses in scale-free networks[J]. Physical Review E, 2002,65:055103(R).
[24] Cohen R, ben-Avraham D, Havlin S. Efficient Immunization Strategies for Computer Networks and Populations[J]. Physical Review Letters, 2003, 91:247901.
[25] Duan W-Q, Chen Z, Liu Z-R, et al. Efficient target strategies for contagion in scale-free networks[J]. Physical Review E, 2005, 72:026133.
[26] Zanette D H. Dynamics of rumor propagation on small-world networks[J]. Physical Review E, 2002,65:041908.
[27] Moreno Y, NekoveeM, Pacheco A F. Dynamics of rumor dissemination in complex networks[J]. Physical Review E, 2007, 69:066130.
[28] Barabasi A-L, Bonabeau E. Scale-Free Networks[J]. Scientific American, 2003, 288: 60-69.
[29] Niloy Ganguly, Biplab K Sikdar,Andreas Deutsch ,Geoffrey Canright ,P Pal Chaudhuri .A Survey on Cellular Automata[Z].
[30] WolframS. Statistica mechanics of cellular automata. http://stephenwolfram.com/publications articles/ca/83-statistical/, 2001.
[31]于乃功,阮晓钢.细胞自动机及其在复杂系统研究中的应用[J].计算机工程与应用, 2004.(12):25-28.
[32] Michael D Santoro,ShanthiGopalakrishnan.The institutionalization of knowledgetransfer activities within industry-university collaborative ventures[J].Journal of Engineering and Technology Management,2000,17:299-319.
[33]丹尼斯·麦奎尔,斯文·温德尔.祝建华,武伟译.大众传播模式论[M].上海译文出版社,1987.
[34]艾森伯格,古多尔.组织传播一平衡创造性和约束[M].北京:北京广播学院出版社,2004.