基于超网络模型的网络舆论本体“噪声”识别  

An Opinion-Noise Detection Supernetwork Model

作　　者：廉莹 董雪璠 侯胜杰 LIAN Ying;DONG Xuefan;HOU Shengjie(School of Journalism,Communication University of China,Beijing 100024;College of Economics and Management,Beijing University of Technology,Beijing 100124;National Innovation Institute of Defense Technology,Academy of Military Science,Beijing 100071)

机构地区：[1]中国传媒大学新闻学院,北京100024 [2]北京工业大学经济与管理学院,北京100124 [3]军事科学院国防科技创新研究院,北京100071

出　　处：《系统科学与数学》2023年第8期2086-2102,共17页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(72274010);中国传媒大学中央高校基本科研业务费专项资金(201/CUC230B001);北京市学校思想政治工作研究课题(XXSZ2022YB45)资助课题。

摘　　要：网络舆论的研究既应重视数量也应重视质量,在纷繁复杂的舆论大数据中寻找高质量的网络舆论是对新网络舆论观的践行.以网络舆论质量三维评价体系为理论基础,通过对舆论超网络模型节点和连边的改变和重构,提出了网络舆论本体“噪声”超网络识别模型,涉及环境子网、情绪子网、社交子网和内容子网.网络舆论本体“噪声”是指无法对管理决策的制定提供意见和建议的舆论观点.基于所提出的超网络模型,提取18个特征指标,并利用机器学习分类算法实现对高质量舆论观点的提取.As looking for high-quality online public opinions from mass reticula data is the practice of the new concept of online public opinion,both quantity and quality aspects should be considered by relevant studies.Based on the three-dimensional evaluation system of the quality of online public opinion,through the change and reconstruction of the nodes and edges of the public opinion supernetwork model,an Opinion-Noise Detection Supernetwork model was proposed,in which there are four subnetworks:Environmental subnetwork,emotional subnetwork,social subnetwork and content subnetwork.The noumenon of online public opinion“noise”refers to the public opinion data that cannot provide suggestions for the formulation of management decisions.Based on the proposed model,18 characteristic indexes were extracted.Finally,by employing machine learning algorithms,the public opinions with high quality were successfully identified.

关 键 词：网络舆论 舆论质量 超网络 机器学习 

分 类 号：C912.63[经济管理] TP391.1[社会学] O157.5[自动化与计算机技术—计算机应用技术]