大数据2026，Vol.12Issue(1)：29-42,14.DOI:10.11959/j.issn.2096-0271.2026012
面向时序数据的多维度网络舆情演化分析研究
Research on online public opinion evolution analysis of multi-dimensional for time series data
摘要
Abstract
A multi-dimensional framework for analyzing the evolution of online public opinion was proposed,aiming to address the limitations in current research,such as a single perspective,incomplete topic mining,shallow sentiment analysis,and inaccurate identification of group behavior.Firstly,the four life cycle stages of public opinion evolution were divided based on social influence.Secondly,the topic evolution process was analyzed using the BERTopic model and similarity calculation.Sentiment fluctuations were studied by leveraging large language models.User groups were classified and opinion leaders were identified based on interaction relationships.Finally,the differences in social influence and sentiment across different periods and regions were visualized.Taking the event of''adjustment of stamp duty''in temporal public opinion data as an example,the study discovered that the topics of public concern,sentiment tendencies,user groups,and opinion leaders changed during the four life cycle stages of public opinion.The sentiment response in eastern regions was more positive,and the duration of public opinion topics and sentiments was longer.This study can provide technical support for revealing the laws of public opinion evolution and implementing effective public opinion monitoring.关键词
时序数据/网络舆情/多维度演化/主题演化/情感波动/用户群体Key words
time-series data/online public opinion/multidimensional evolution/topic evolution/sentiment fluctuation/user group分类
自科综合引用本文复制引用
李旸,王志华,李大宇,赵鑫,詹雅慧,王素格..面向时序数据的多维度网络舆情演化分析研究[J].大数据,2026,12(1):29-42,14.基金项目
国家自然科学基金项目(No.62376143) （No.62376143）
山西省基础研究计划项目(No.202503021211239,No.202203021212499) The National Natural Science Foundation of China(No.62376143),The Shanxi Provincial Basic Research Program Project(No.202503021211239,No.202203021212499) （No.202503021211239,No.202203021212499）
