复杂网络新特征在虚拟社区分析中的应用

Zhen Zhang, Qing-chun Meng, Xiaoxia Rong, V. C. Lee
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引用次数: 0

摘要

虚拟社区(Virtual community, VC)迅速兴起,影响着现实世界中人们生活方式的方方面面。与传统的产品/服务广告方式不同,VC还可以让消费者通过线程参与到与产品相关的互动活动中,更深入地了解产品,提高消费者的忠诚度。现有的研究大多缺乏对产品深度学习的重视或缺乏有效的方法来解释VC中用户重要性的一致性。本文基于复杂网络的知识,提出了有向网络广义度方差来确定有向网络的均匀性,这是一种创新的方法。研究结论可以指导企业更深入地理解复杂网络理论及其在大数据流社会网络分析(SNA)中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Novel Features in Complex Network for Analyzing Virtual Community
Virtual community (VC) arises rapidly and influences many aspects of human life styles in real world. Differentiated from traditional way to advertise products/services, VC also enables consumers to participate in interaction activities related to products via threads, learn greater insight about products in deep level while improve consumer loyalty. Most of the extant research did not emphasize or lack of effective methods on how to gain deep learning of product and explain the uniformity of users’ importance in VC. In this paper, based on knowledge in complex network, generalised variance of degree in directed network is proposed to ascertain uniformity of directed network, which is an innovative methodology. Research conclusions can guide enterprises more in-depth understanding of the complex network theory and its application to social network analysis (SNA) with big data streams.
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