Open AccessApplication of Novel Features in Complex Network for Analyzing Virtual Community
Author(s) -
Zhen Zhang,
Qingchun Meng,
Ximin Rong,
Vincent. C. S. Lee
Publication year - 2020
Publication title -
international journal of e-education, e-business, e-management and e-learning
Language(s) - English
Resource type - Journals
ISSN - 2010-3654
DOI - 10.17706/ijeeee.2020.10.4.312-320
Subject(s) - extant taxon , computer science , complex network , loyalty , product (mathematics) , data science , variance (accounting) , virtual community , social network analysis , knowledge management , world wide web , marketing , social media , business , the internet , mathematics , geometry , accounting , evolutionary biology , biology
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.