基于从属关系的社交问答平台知识子群研究

The Research of Knowledge Subgroups in Social Question and Answer Site Based on Affiliation

摘要:

虚拟社区的快速发展,使得大量自发形成的知识被显性化或多次再创造。本文关注如何运用社会网络的原理,提炼并发现社交问答平台中的知识的问题。以社交问答平台“知乎”网为例,利用社区中现存的从属关系数据,即社区中提出的问题、及问题回答者之间的关系,建立网络模型,强调了网络中的联系强度与问答交互行为。同时基于社会网络的凝聚特性,补充了 “知识子群”的概念。研究表明,(1)在社交媒体的研究中,应更注重成员的交互行为而不只是相互关注行为,(2)运用从属关系建模方法,能够体现成员之间的交互强度,(3)基于多重连线值能有效找到知识网络节点中的内在联系与相似程度,以实现知识发现与分类的目的。

Abstract:

With the rapid development of virtual communities, lots of knowledge has been expressed or produced many times. This paper focuses on how to extract and discover the knowledge in social question and answer site, with the theory of social network. According to the existing data of affiliation, there are numerous relationships between the questions and their answers in the community. This paper took “Zhihu”, as a social question and answer site for example, and built the net model, which emphasized the level of communication and the interbehavior of question and answer. Meanwhile, based on the cohesion of social network, this paper put forward the concept about “knowledge subgroups”. The result shows that: (1)the research in social website prefer to focuses on the interbehavior than the behavior of follow each other, (2)the method of affiliation modelling could reflect on the level of communication among members, (3)it could found the inner connection and the level of similarity among nodes of knowledge network based on the value of multiple lines, in order to accomplish the knowledge discovery and classification.