基于复杂网络的微博网络舆情图谱分析方法研究

A Study of Complex-network-based Graph-analytical Approach on Microblog Net-mediated Public Sentiment

本文针对微博网络舆情的控制和引导问题,提出一种基于复杂网络的图谱分析方法。本文以微博用户间转发和评论某一话题下用户关系数据作为基础研究数据,生成用户节点网络关系图谱,通过对微博网络模块化图谱、路径图谱和中心性图谱分析,定性和定量评估出对舆情活跃度高、传播范围广、传播速度快的微博用户节点,作为控制微博舆情的传播、引导舆情舆论导向的关键用户节点。本文以某一微博社区为样本数据,采用复杂网络分析工具Gephi,验证了基于复杂网络的图谱分析对识别舆情控制中关键用户节点的正确性和有效性。

Considering how to control and guide microblog net-mediated public sentiment,a complex-network-based graph-analytical approach was proposed. Based on the analysis of relationship data generated by users that commented on and forwarded one topic of the microblog,graphs of user nodes network are built,and by analyzing the modularity graph,path graphs and centrality graphs,user nodes that are highly active on public sentiment and have wide breadth propagation,deep depth propagation and fast speed propagation are evaluated quantitatively and qualitatively. Besides,these nodes are controlled and guided effectively,which may be used to slowly spread the net-mediated public sentiment and guide the direction of the public topic. Taking some microblog community data as sample data,and using complex network software Gephi as analysis tool,the correctness and effectiveness of the a complex-network-based graph-analytical approach which was used to identify the key nodes in the process of the public sentiment control were verified.