构建基于模糊聚类算法的网络情绪动态分析系统  

Constructing a Network Emotion Dynamic Analysis System Based on Fuzzy Clustering Algorithm

作　　者：薛淼 段立娟[1] XUE Miao;DUAN Lijuan(Beijing University of Technology,Beijing 100124,China)

机构地区：[1]北京工业大学,北京100124

出　　处：《现代信息科技》2025年第5期95-98,104,共5页Modern Information Technology

摘　　要：网络情绪动态分析研究可以通过分析网络文本中的情绪语义表达来实现。构建基于模糊聚类算法的网络情绪动态分析系统,需要以情绪语义模板为基础,利用爬虫软件获取个体或群体在社交网络上的文本数据。在对情绪状态进行数值化处理的基础上,利用模糊聚类(FCM)算法进行情绪状态的聚类分析,并根据聚类结果识别网民的情绪状态及其变化趋势。该系统由情绪语义模板生成模块、数据采集模块、数据预处理模块和模糊聚类分析模块组成,可为社会管理和危机干预提供决策支持。The research of network emotion dynamic analysis can be realized by analyzing the emotional semantic expression in the network text.To construct a network emotion dynamic analysis system based on Fuzzy C-Means algorithm,it is necessary to use crawler software to obtain the text data of individuals or groups on social networks based on the emotional semantic template.Based on the numerical processing of emotional state,the Fuzzy C-Means(FCM)algorithm is used to cluster the emotional state,and the emotional state and its change trend of netizens are identified according to the clustering results.The system consists of emotional semantic template generation module,data acquisition module,data preprocessing module and fuzzy clustering analysis module,which can provide decision support for social management and crisis intervention.

关 键 词：模糊聚类算法 标准分 网络情绪 动态分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]