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Received:July 09, 2020 Revised:August 11, 2020
Received:July 09, 2020 Revised:August 11, 2020
中文摘要: 从宏观角度研究基于关键词的网络舆情热度有助于相关机构把握目标群体的整体舆情动态, 从而实现精准施策, 提升舆论引导水平. 本文以新浪微博数据为例, 采用因子分析方法(Factor Analysis, FA), 挖掘舆情热度内在影响因素, 并通过改进Elman网络结构, 利用遗传算法(Genetic Algorithm, GA)优化初始参数来构建模型对网络舆情关键词热度进行分析预测. 实验结果表明, 所提出的方法相较于采用原始数据集和标准Elman网络的预测结果, 具有更高的预测精度, 可为相关研究提供决策支持.
Abstract:It is helpful for institutions to master the whole trends of target group that research on keywords popularity of network public opinions from a macroscopic perspective, precisely formulating corresponding strategies to enhance the level of opinion guidance. With Sina Weibo data set as an example, Factor Analysis (FA) is used to mine the internal factors of public opinions; a model that analyzes and predicts the keyword popularity of network public opinions is created through the initial parameters optimized by Genetic Algorithm (GA) and Elman network structure. The results show that predictions made by our method is more precise than those of original data sets and standard Elman network. Thus, it can be applied to providing reference for decision making.
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基金项目:全国教育信息技术研究重点课题(183220001)
引用文本:
肖光华,王清莲.基于因子分析和Elman网络的舆情关键词热度预测.计算机系统应用,2021,30(3):243-249
XIAO Guang-Hua,WANG Qing-Lian.Prediction on Keywords Popularity of Public Opinion Based on Factor Analysis and Elman Network.COMPUTER SYSTEMS APPLICATIONS,2021,30(3):243-249
肖光华,王清莲.基于因子分析和Elman网络的舆情关键词热度预测.计算机系统应用,2021,30(3):243-249
XIAO Guang-Hua,WANG Qing-Lian.Prediction on Keywords Popularity of Public Opinion Based on Factor Analysis and Elman Network.COMPUTER SYSTEMS APPLICATIONS,2021,30(3):243-249