[Objective] This study aims to identify the key nodes of public opinion spread and evolution based on the semantic social network model. [Methods] We first built model for Weibo semantic social network with the help of hypernetwork theory, and then used emotion Ontology and LDA model to quantify nodes. Finally, we established the hyper edge sorting algorithm to identify the key nodes. [Results] The proposed model could effectively and acturately quantify those nodes from real Weibo data. [Limitations] We did not explore the results of the proposed method’s real-time performance, and new ways of leading the public opinion after identifying those key nodes. [Conclusions] This study provides a solution for the government to identify the key nodes in the social network systems, and then reduce the impacts of negative contents to the healthy development of the Internet.
张磊,马静,李丹丹,沈洋. 语义社会网络的超网络模型构建及关键节点自动化识别方法研究*[J]. 现代图书情报技术, 2016, 32(3): 8-17.
Zhang Lei,Ma Jing,Li Dandan,Shen Yang. Hypernetwork Model for Semantic Social Network and Automatic Identification of Key Nodes. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2016.03.02.
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