基于社会网络分析的虚实社区特性研究
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摘要
由互联网媒体中介形成的虚拟社区创造了人际交往的新平台以及人际互动的全新模式。然而,随着人们对沟通交流的需要以及对真实感的追求,虚拟社区成员以及社区的倡导者开始开辟新的沟通方式,即通过虚拟社区平台互动,然后延伸至现实中进一步沟通交流。这形成了介于虚拟与现实的另一种崭新的社区模式,本研究称之为“虚实社区”。
虚实社区成员之间实际存在或者潜在的关系模式,即为社会网络结构。在收集了调查问卷后,本研究先利用Ucinet6软件计算出社会网络结构的相关指标,即聚类系数、特征途径长度、网络密度。同时对代表权力集中趋势的三项指标点度中心性、中间中心性、接近中心性进行了计算,并在此基础上分析了核心成员角色变化状况。
虚实社区社会网络结构特征(聚类系数、特征途径长度、网络密度、点度中心势、中间中心势、接近中心势)会影响成员心理以及行为,包括人际交互、归属感、自我认同。基于社区特性的社会性角度考虑,这几个因素恰是影响社区特性的要素。因此对网络结构特征和社区特性的相关关系进行了必要的研究,其结论对提高虚实社区成员参与以及社区管理水平有理论和实践意义。
本研究先后对数据进行了探索性因子分析、信度分析、效度分析,相关性分析。最后在此基础上,运用回归模型进行假设检验。得到了如下结论:聚类系数和网络密度对人际交互、归属感、自我认同有正向影响。特征途径长度对归属感、自我认同有负向影响,对人际交互无显著影响。点度中心势、接近中心势均与人际交互、归属感、自我认同呈反比。而中间中心势只对前两者有负向影响。
研究结论对分析核心成员角色和虚实社区特性提供了理论依据。本研究针对实证研究分析的结果进行了理论意义的解释,提出一系列建议。如加强社区人际互动;建立规范的社区制度和行为准则;形成良好的社区沟通机制;建立丰富多样的社区活动形式;指出虚实社区管理者要重视情感的作用,同时关注成员中的孤立点,避免对社区特性产生不利影响。
The Internet media intermediary form virtual community,which creates a new platform of interpersonal communication and a new mode of interpersonal interaction. However, with the need of communication and the pursuit of the reality,the virtual community members and advocates begin to open up new way of communication。Namely, through the virtual community platform, members extend to reality for further communication. This form another new community mode called vir-true community between virtual and reality.
In vir-true community, the relationship model of the actual or potential existence can be defined as a social network structure. After collecting some questionnaires, this article firstly use Ucinet6 to analyse network structure index ,such as clustering coefficient , the characteristic path length and density. And figure out degree centralization, betweenness centralization and closeness centralization ,which on behalf of the concentrated power.The changes of central role is analyzed based on the analysis.
Social network structure feature(clustering coefficient,the characteristic path length, density, degree centralization, betweenness centralization and closeness centralization)affect the psychological and behavior of members, including the interpersonal interaction , sense of belonging , and self-identity.From the social perspective of community feature,these factors can affect community feature. So we consider that some conformity researches on relations between network structure feature and community feature mentioned above need to be made, which conclusions will be used for raising community particiapation and management level.
We conduct exploratory factor analysis,reliability analysis,validity analysis and correlation analysis . On this basis,we use regression analysis to conduct hypothesis testing.And get the conclusion that clustering coefficient and density has positive influence on interpersonal interaction, sense of belonging, and self-identity. The characteristic path length has negative influence on sense of belonging and self-identity.,but no clear influence on interpersonal interaction. Degree centralization and closeness centralization are in reverse proportion with interpersonal interaction, sense of belonging and self-identity.But betweenness centralization merely has negative influence on interpersonal interaction and sense of belonging.
Research conclusions provide a theoretical basis for analyzing changes of central role and vir-true community feature.The study make the explanation on the theory and provide some suggestion.For example, the community should improve interpersonal interaction;establish canonical community system and codes of conduct;form a good communication mechanism;build rich variety of community activities.Conclusions also advise managers to pay attention to friendship.At the same time,isolated point in the organization should be concerned to avoid the adverse effect on vir-true community feature.
虚实社区成员之间实际存在或者潜在的关系模式,即为社会网络结构。在收集了调查问卷后,本研究先利用Ucinet6软件计算出社会网络结构的相关指标,即聚类系数、特征途径长度、网络密度。同时对代表权力集中趋势的三项指标点度中心性、中间中心性、接近中心性进行了计算,并在此基础上分析了核心成员角色变化状况。
虚实社区社会网络结构特征(聚类系数、特征途径长度、网络密度、点度中心势、中间中心势、接近中心势)会影响成员心理以及行为,包括人际交互、归属感、自我认同。基于社区特性的社会性角度考虑,这几个因素恰是影响社区特性的要素。因此对网络结构特征和社区特性的相关关系进行了必要的研究,其结论对提高虚实社区成员参与以及社区管理水平有理论和实践意义。
本研究先后对数据进行了探索性因子分析、信度分析、效度分析,相关性分析。最后在此基础上,运用回归模型进行假设检验。得到了如下结论:聚类系数和网络密度对人际交互、归属感、自我认同有正向影响。特征途径长度对归属感、自我认同有负向影响,对人际交互无显著影响。点度中心势、接近中心势均与人际交互、归属感、自我认同呈反比。而中间中心势只对前两者有负向影响。
研究结论对分析核心成员角色和虚实社区特性提供了理论依据。本研究针对实证研究分析的结果进行了理论意义的解释,提出一系列建议。如加强社区人际互动;建立规范的社区制度和行为准则;形成良好的社区沟通机制;建立丰富多样的社区活动形式;指出虚实社区管理者要重视情感的作用,同时关注成员中的孤立点,避免对社区特性产生不利影响。
The Internet media intermediary form virtual community,which creates a new platform of interpersonal communication and a new mode of interpersonal interaction. However, with the need of communication and the pursuit of the reality,the virtual community members and advocates begin to open up new way of communication。Namely, through the virtual community platform, members extend to reality for further communication. This form another new community mode called vir-true community between virtual and reality.
In vir-true community, the relationship model of the actual or potential existence can be defined as a social network structure. After collecting some questionnaires, this article firstly use Ucinet6 to analyse network structure index ,such as clustering coefficient , the characteristic path length and density. And figure out degree centralization, betweenness centralization and closeness centralization ,which on behalf of the concentrated power.The changes of central role is analyzed based on the analysis.
Social network structure feature(clustering coefficient,the characteristic path length, density, degree centralization, betweenness centralization and closeness centralization)affect the psychological and behavior of members, including the interpersonal interaction , sense of belonging , and self-identity.From the social perspective of community feature,these factors can affect community feature. So we consider that some conformity researches on relations between network structure feature and community feature mentioned above need to be made, which conclusions will be used for raising community particiapation and management level.
We conduct exploratory factor analysis,reliability analysis,validity analysis and correlation analysis . On this basis,we use regression analysis to conduct hypothesis testing.And get the conclusion that clustering coefficient and density has positive influence on interpersonal interaction, sense of belonging, and self-identity. The characteristic path length has negative influence on sense of belonging and self-identity.,but no clear influence on interpersonal interaction. Degree centralization and closeness centralization are in reverse proportion with interpersonal interaction, sense of belonging and self-identity.But betweenness centralization merely has negative influence on interpersonal interaction and sense of belonging.
Research conclusions provide a theoretical basis for analyzing changes of central role and vir-true community feature.The study make the explanation on the theory and provide some suggestion.For example, the community should improve interpersonal interaction;establish canonical community system and codes of conduct;form a good communication mechanism;build rich variety of community activities.Conclusions also advise managers to pay attention to friendship.At the same time,isolated point in the organization should be concerned to avoid the adverse effect on vir-true community feature.
引文
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[3]何小明.讼虚拟社区中的青少年行为与心理[J].广西师范大学学报,2003,4.
[4]程恩富,彭文兵.社会关系网络:企业新的资源配置形式[J].上海行政学院,2002,(02).
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[7]周德明等.虚拟社区:传统社区概念的拓展[J] .湖湘论坛,2003,1.
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[9]毕雨,王延清.基于虚拟协作社区的虚拟组织中信息资源管理初探[J] .商场现代化.2007,522:21.
[10]王卫东.关于互联网方法和行为的研究[D].中国人民大学博士研究生学位论,2003:17 .
[11] LeUnes, A. D., & Nation, J. R. Sport psychology. Chicago[M], Illinois: Nelson-Hall.
[12] Nahapiet, Janine and Sumantra Ghoshal. Social Capital, Intellectual Capital and the Organizational Advantage [J]. The Academy of Management Review. 1998,23(2):242-266.
[13]林荣钦.管理心理学[M].台北:五南图书出版公司,1992.
[14] Lindquist ,Meredith and Jane Summers ,Andy koronios ,Michael Gardiner, Critical success factor for regional community portals:a preliminary model[J].Americas Conference, 2002, 84-86.
[15]刘军.社会网络分析导论[M].北京:社会科学文献出版社,2004.
[16] Wellman Barry ,Keith,Hampton. Living networks on an offline[J]. Contemporary Sociology,1999:28.
[17] Mitchell J Clyde. The Concept and Use of Social Networks.Manchester University Press for Institute of Social Research[M], University of Zambia,1969.
[18]彭文兵.社会关系网络[J].上海行政学院学报.2002,3.
[19]王霄宁.基于社会网络分析的产业集群定量化模型[J].统计与决策,2005,(06).
[20]王志亮.社会网络分析方法在科研协作网中的应用研究[D].大连理工大学硕士论.2006.
[21]约翰.斯科特.社会网络分析法[M]刘军译.重庆:重庆大学出版社,2007.
[22] Luo Jar-Der, Hui Wei-Sheng and Yeh Kuan-Ling. Social Network Structure and Feature of Knowledge Teams-a Case Study in the Chinese Cultural Settings [C]. American Academy ofManagement Convention, Technology and Innovation Management Session, Seattle, August 1st-6th.
[23]卓秀足,陈沁怡,杨仁寿.社会网络密度和群体中心性对团体效能的影响-以某休闲餐厅为例[C].第四届21世纪产业经营管理国际学术研讨会论文. 2005.
[24]廖镱鈤.虚拟社区的凝聚力[J].E-soc Journal,2002,(11):50-53.
[25]包昌火,谢新洲,申宁.人际网络分析[J].情报学报,2003(6):365-374.
[26] Leimeister,Jan Marco and Pascal Sidiras,Helmut Krcmar,Success factor of virtual communities from the perspective of members and operators:An empirical study.[J]Proceedings of the 37th Hawaii International Conference on system Sciences-2004.
[27] Hernandes,Carols Alberot and Paulo Sérgoi Fresneda .Main Critical Success Facotrsf or the Establishmen tand Operation of Virtual Communities of Practice[C].3rd European Knowledge Management Summer School 17 - 12 Sept ,San Sebastain: 2003.
[28] Wellman, B,&Berkowitz, S. D.. Social Structures: A NetworkApproach [M] . Cambridge, England: Cambridge University Press, 1998.
[29] Berkowitz, S. D. .An Introduction to Structural Analysis: The Network Approach to Social Research [M] . Torento Butterworths, 1983.
[30] Scott, J. . Social NetworkAnalysis: A Handbook [M] . Thousand Oaks: Sage Publications, 2000.
[31]刘军社会网络分析导论[M]北京社会科学文献出版社,2001.
[32]朱庆忠.社会关系网络对组织公民行为影响之探讨[D].元智大学资讯社会学研究所未出版硕士论文,2003.
[33] Wasserman.S.Social network analysis:Methods and applications[M].New York:Cambridge University Press,1944.
[34] Wasserman,S.& Faust,K..Social NetworkAnalysis: Methods and Application [M]. Cambridge: Cambridge University Press, 1994b.
[35]冯锐,谢英香.当代大学生虚拟与现实社会人际关系的差异性分析[J].现代教育技术,2009,(1):28-32.
[36]罗家德.社会网络分析讲义[M].北京:社会科学文献出版社,2005.
[37] Pastor-Satorras R, Vespignani Evolution andStructure of the Internet:A Statistical Physics Approach(Cambridge: Cambridge University Press, 2004.
[38]刘军.整体网分析讲义[M].北京:上海人民出版社,2009.
[39] Freeman.L. The sociological concept of group:An empirical test of two modles[J].American Journal of Sociology,1992,(98):152-166.
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