从成员中心性探究虚拟社会网络中成员传播力的形成机制
A Study on the Formation Mechanism of Dissemination Force in Virtual Social Network from the Angle of Node Centrality

作者: 孙培翔 , 彭 捷 :武汉大学经济与管理学院,武汉;

关键词: 虚拟社会网络中心性传播力意见领袖网络营销Virtual Social Network Node Centrality Dissemination Force Opinion Leaders Network Marketing

摘要:
文章从成员中心性的角度对虚拟社会网络中成员传播力的形成机制进行了探究,通过社会网络分析和Tobit回归,结论表明:成员的度中心性(粉丝关注数量)和桥中心性(占据网络最短路径的数量)正向促进其网络传播力;接近中心性(网络中成员距其他成员物理位置的远近)则对传播力无影响。理论上,文章明确了成员所占据的网络结构位置和资源在很大程度上决定了其传播力;实践上,我们可以根据成员的网络中心性来更好地挖掘和识别网络领袖,从而发挥其传播力来进行网络营销。

Abstract: This study investigates the formation mechanism of dissemination force and the influence models of nodes’ network centrality in the virtual social network. Combining the Social Network Analysis and Tobit regression, we find that: 1) both a node’s degree centrality and betweenness centrality have a positive impact on its dissemination force; 2) the closeness centrality didn’t. For theory contribution, we have a clever understand of the source of member’ dissemination force and the various influence models of different node centralities in virtual social network. For practice contribution, different kinds of opinion leaders can be distinguished according to different centralities in a more accurate way, so that we can make a more effective use of their dissemination force in network marketing.

文章引用: 孙培翔 , 彭 捷 (2014) 从成员中心性探究虚拟社会网络中成员传播力的形成机制。 财富涌现与流转, 4, 49-55. doi: 10.12677/ETW.2014.44007

参考文献

[1] Kaplan, A.M. and Haenlein, M. (2010) Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53, 59-68.

[2] Granovetter, M. (1973) The strength of weak ties. American Journal of Sociology, 78, l360-1380.

[3] Stephen, A.T. and Toubia, O. (2010) Deriving value from social commerce networks. Journal of Marketing Research, 47, 215-228.

[4] Curty, R.G. and Zhang, P. (2011) Social commerce: Looking back and forward. Proceedings of the American Society for Information Science and Technology, 48, 1-10.

[5] Brass, D.J., et al. (2004) Taking stock of networks and organizations: A multilevel perspective. Academy of Management Journal, 47, 795-817.

[6] Ransbotham, S., Kane, G.C. and Lurie, N.H. (2012) Network characteristics and the value of collaborative user-generated content. Marketing Science, 31, 387-405.

[7] Armstrong, A. and Hagel, J. (2000) The real value of online communities. Knowledge and Communities, 85-95.

[8] Goldenberg, J., Han, S., Lehmann, D.R., et al. (2009) The role of hubs in the adoption process. Journal of Marketing, 73, 1-13.

[9] Katona, Z., Zubcsek, P.P. and Sarvary, M. (2011) Network effects and personal influences: The diffusion of an online social network. Journal of Marketing Research, 48, 425-443.

[10] Kumar, V., et al. (2013) Creating a measurable social media marketing strategy for hokey pokey: Increasing the value and ROI of intangibles and tangibles. Marketing Science, 32, 194-212.

[11] Krackhardt, D. (1998) Simmelian ties: Super strong and sticky. Power and Influence in Organizations, 21-38.

[12] Coleman, J.S. (1988) Social capital in the creation of human capital. American Journal of Sociology, 94, S95-S120.

[13] Burt, R.S. (2009) Structural holes: The social structure of competition. Harvard University Press, Cambridge.

[14] Freeman, L. (1977) A set of measures of centrality based upon betweenness. Stoichiometry, 40, 35-41.

[15] Borgatti, S.P., et al. (2009) Network analysis in the social sciences. Science, 323, 892-895.

[16] Newman, M.E.J. (2005) A measure of betweenness centrality based on random walks. Social Networks, 27, 39-54.

[17] Trier, M. (2008) Towards dynamic visualization for understanding evolution of digital communication networks. Information Systems Research, 19, 335-350.

[18] Brandes, U. (2001) A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25, 163-177.

[19] Sabidussi, G. (1966) The centrality index of a graph. Psychometrika, 31, 581-603.

分享
Top