基于社会网络分析的网络问答社区知识传播研究

Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis

[目的]通过分析网络问答社区的社会网络结构和知识传播机制,研究节点在网络问答社区的知识传播与学习的效用,从而指导用户在网络问答社区中更高效地学习。[方法]结合社会网络分析方法和熵权法描绘意见领袖的知识能力和传播影响力,而后针对网络问答社区社会网络的小世界特征,在借鉴Cowan模型的基础上建立一个知识传播模型,并通过系统模拟仿真对该网络内部的知识学习效果进行实验。[结果]知识存量越少的节点在网络中的学习效率越高,该现象类似于森林的"海绵效应";一些节点的知识存量增长较快,其知识存量的增长倍数远远大于那些当初知识存量较高的节点;随着时间的增长,网络的知识传播速率一直处于下降的趋势;知识增量与知识能力指数和传播能力指数都有很强的关系。[局限]在关于传播动力学模型的假设上,本文未考虑到网络的动态随机重连。[结论]本文较为客观地评价了网络问答社区的知识传播与学习效用的情况,并提出相应建议以提升用户在网络问答社区中的学习效果。

[Objective]This paper analyzes the social network structure and knowledge dissemination mechanism of an online Q&A community, aiming to reveal the role of network nodes, and improve the learning efficiency. [Methods] First, we used the social network analysis and the entropy weight methods to describe the opinion leader’s knowledge and influence. Then, we built a knowledge dissemination model based on the Cowan model for the Q&A community. Finally, we examined the internal knowledge learning results of the network through system simulation. [Results] Ⅰ. The nodes with less knowledge had higher learning efficiency in the target network; Ⅱ. The knowledge volumes of some nodes increased rapidly, while those of the nodes with larger knowledge stock increased slowly; Ⅲ. The knowledge dissemination rate of this network has been decreasing; Ⅳ. There is strong correlation between knowledge increase and the index of knowledge and communication abilities. [Limitations] The dynamic random reconnection of network was not examined in this paper. [Conclusions] This paper offers practical advice to improve users’ learning experience in the online Q&A community.