网络论坛视角下突发事件舆情的关键节点识别及分类研究

Research of Identification and Classification of Emergencies Key Nodes Based on BBS

认为在突发事件的舆情传播过程中,网络论坛中影响力大的关键节点左右传播的走势。设计一种完整的网络舆情节点挖掘和分类的技术方法,包括原始数据挖掘、数据结构化、节点影响力测算与识别、关键节点论坛影响力计算、关键节点分类等,涉及GooSeeker、Gephi、LeaderRank等算法和软件,并以"7·23动车事故"为例进行具体分析。通过研究揭示出网络舆情的结构复杂性、无标度性、子社区结构等特征,得到"网络名人型"和"事件关注型"两类关键节点的演化规律,对网络舆情的科学应对具有参考价值。

In the information spread process of emergencies, the powerful key nodes in BBS often decide the spread trend of Internet public opinion. This paper designed a technical method which integrating data mining, data structure, node measuring and recognition, key nodes influence calculation, key node classification etc. , involving the algorithm and software such as GooSeeker, Gephi, LeaderRank, taking the 723 train accident as the example. It revealed the characteris- tics of network public opinion including the complexity of structure, scale-free and community structure etc. , and got two kinds of key nodes as ＂web celebrities＂ and ＂event focus＂. This has the reference value to the network public opinion re- sponse.