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基于网络闭包理论的交易型社区网络演化研究 被引量:5

Network evolution of transactional community based on network closure theory
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摘要 随着社会化商务时代的到来,交易型社区的发展越来越成为解决社会化商务中经济性与社会性矛盾的关键.但交易型社区与传统社交社区在成员角色和动机上的差异性也导致其网络演化的特殊性.本研究以国内最大的交易型网站(淘宝网)为平台,选取其中最活跃的圈子社区之一(共7902名会员,有效样本为6195名会员)为研究对象,分析交易型社区网络闭包机制相对于传统社交网络闭包机制的差异性.研究结果表明:(1)由于互惠关系的形成可能需要较高的交互成本并带来关系依赖和关系无效率的风险,交易型社区中成员会回避互惠关系的形成;(2)在一个主要由陌生人组成的交易型社区的模糊情境下,信息性社会影响起着主要作用,信息源的传播路径越多一方面加强了信息源的传染性,但另一方面也降低了该信息源的必要性而不利于其他成员与其构建关系;(3)交易型社区网络闭包(关系构建)的主要动力来源于成员间的相似性(选择性影响),具体表现在共同的社区好友和共同参与的社区活动上. As the era of social commerce is coming,the transactional community has become a key solution to the contradiction between economic nature and social nature in social commerce.Traditional social network analysis explored the evolution of social network,while transactional community is very different from social community regarding the roles and motivations of their members.This research,based on one of the most active communities in Taobao.com,analyzed the differences of transactional community in network closure mechanism.The results showed:(1) Members in transactional community would choose to avoid reciprocity because of high cost of social interaction and the risk of inefnciency of relationship;(2) In a vague situation where informational social influence impacts the most,more options of contagion path would enhance influence but harm necessity of its member,which has a negative effect on relationship estabUshment;(3) The relationship establishment in transactional community comes mainly from the similarities among members,which include the mutual acquaintances or mutual activities.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2015年第5期1165-1176,共12页 Systems Engineering-Theory & Practice
基金 国家自然科学基金(71372127) 海外及港澳学者合作研究基金(71328203) 教育部新世纪优秀人才项目(NCET-12-0420) 武汉大学自主科研项目(2013105010212)
关键词 交易型社区 网络闭包 互惠性 传染性 选择性 transactional community network closure reciprocity contagion selection
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  • 1Aral, S., Walker, D., 2012, "Identifying Influential and Susceptible Members of Social Networks" , Science, VoL337 (6092), pp.337- 341.
  • 2Bala, V., Goyal, S., 2000, "A Noncooperative Model of Network Formation", Econometrica, Vol.68 (5), pp. 1181 - 1229.
  • 3Barabetsi, A. L., 2012, "Network Science. Luck or Rea- son',Nature, Vol.489 (7417), pp.507-508.
  • 4Barabctsi, A. L., Albert, R., 1999, "Emergence of Scal- ing in Random Networks", Science, Vol.286 ( 5439 ), pp.509-512.
  • 5Borgatti, S. P., Mehra, A., Brass, D. J., 2009, "Network Analysis in The Social Sciences", Science, Vol.323 (5916) , pp.892-895.
  • 6Burt, R., 1987, "Social Contagion and Innovation. Cohe- sion Versus Structural Equivalence" ,American Journal of Sociolo- gy, Vol.92(6), pp.1287-1335.
  • 7Burt, R., 1992, Structural Holes, Cambridge, MA. Har- vard University Press.
  • 8Chevalier, J. A., Mayzlin, D., 2006, "The Effect of Word of Mouth on Sales. Online Book Reviews", Journal of Marketing Research, Vol.43 ( 3 ), pp.345-354.
  • 9Childers, T. L., 1986, "Assessment of The Psychometric Properties of An Opinion Leadership Scale", Journal of Market- ing Research, Vol.23 ( 2 ), pp. 184-188.
  • 10Cpherson, M. M., Lovin, L. S., Cook, J., 2001, "Bird- sof A Feather. Homophilyin Social Networks" , Annual Review of Sociology, Vol.27 ( 1 ), pp.415-444.

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