Research on the Application of Network Public Opinion Collection and Analysis Based on Text Mining Technology
This article explores the application of text mining technology in the collection and analysis of online public opinion.It discusses the lifecycle theory of online public opinion,related technologies for online public opinion collection and analysis,Chinese word segmentation algorithms,text mining techniques,as well as specific text preprocessing,word frequency analysis,and LDA topic modeling.In the preprocessing of online public opinion data,data quality can be improved through methods such as denoising,custom dictionaries and word segmentation,stop word filtering,etc.Text word frequency analysis utilizes the TF-IDF algorithm to accurately mine keywords and gain a deeper understanding of the importance of public opinion events.LDA topic modeling technology,on the other hand,provides a more profound analysis perspective for public opinion events by discovering topic structures,indicating that establishing a public opinion monitoring and management mechanism can better construct the online public opinion environment.
analysis of online public opiniontext mining technologyLDA theme modeling
NETL
NSTL
万方数据
