| 基于SNA与模糊TOPSIS的网络舆情关键节点识别分类模型研究 |
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| 引用本文： | 彭丽徽,李贺,张艳丰.基于SNA与模糊TOPSIS的网络舆情关键节点识别分类模型研究[J].现代情报,2017,37(8):17-25. |
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| 作者姓名： | 彭丽徽 李贺 张艳丰 |
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| 作者单位： | 1. 吉林大学管理学院, 吉林 长春 130022;2. 长沙师范学院图书馆, 湖南 长沙 410100 |
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| 基金项目： | 吉林大学2015年度基本科研业务费哲学社会科学研究种子基金项目“我国开放存取持续发展的关键问题解析：问题机理、接受模型及政策导向研究”。 |
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| 摘 要： | 目的/意义]在舆情监控和管理的实践过程中，迅速有效地识别出舆情网络中的关键节点，对舆情的监督和治理具有重要意义。方法/过程]从内容与结构双重维度，设计一种完整的网络舆情关键节点挖掘、识别和分类的技术方法。涉及GooSeeker、Gephi、Fuzzy AHP和TOPSIS等软件和算法，并以新浪微博“8·12滨海爆炸”事件为例进行具体分析。结果/结论]突破了单纯从单一维度进行关键节点排序的局限性，使关键节点的识别与分类进一步深入，并明确演化特征，对网络舆情的科学应对具有参考价值。
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| 关 键 词： | 网络舆情 关键节点 识别 分类 社会网络分析 综合评价 |
Research on Network Public Opinion Key Nodes Identification and Classification Model Based on SNA and Fuzzy TOPSIS |
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| Authors: | Peng Lihui Li He Zhang Yanfeng |
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| Institution: | 1. School of Management Jilin University, changchun 130022, China;2. Library, Changsha Normal University, changsha 410100, China |
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| Abstract: | Purpose/significance]In the practice of public opinion monitoring and management,identifying the key nodes in the public opinion network quickly and effectively is of great significance to the supervision and management of public opinion.Method/process]From the dual dimensions of content and structure,this paper designed a complete method for mining,identifying and classifying key nodes of network public opinion.Involving GooSeeker,Gephi,Fuzzy AHP and TOPSIS software and algorithms,and Sina micro-blog 8·12 coastal explosion event as an example for specific analysis.Result/conclusion]It broke through the limitation of sorting only the key nodes from a single dimension,made the identification and classification of key nodes further,and made clear the evolution characteristics,which had reference value to the scientific response of network public opinion. |
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| Keywords: | network public opinion key nodes identification classification social network analysis comprehensive evaluation |
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