Open AccessAnalysis and Mining of Internet Public Opinion Based on LDA Subject Classification
Author(s) -
Mei Zhang,
Huihui Su,
Jia Wen
Publication year - 2021
Publication title -
journal of web engineering/journal of web engineering on line
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.151
H-Index - 13
eISSN - 1544-5976
pISSN - 1540-9589
DOI - 10.13052/jwe1540-9589.20811
Subject(s) - public opinion , python (programming language) , the internet , visualization , computer science , government (linguistics) , subject (documents) , cloud computing , data science , world wide web , information retrieval , artificial intelligence , political science , linguistics , philosophy , politics , law , operating system
This paper uses Python, R language, Gephi and other software to crawl and classify the comment content of Weibo hot search events. Using word cloud, co-occurrence social network graphs, LDA topic classification visualization methods, this paper regularizes and integrates public opinions of hot events. Through this research, we can get the influence of public opinion mediators, public opinion objects, and government forces on the network public opinion and put forward corresponding improvement suggestions. We hope to contribute to the government’s governance and prevention of online public opinion during the spread of COVID-19 and other public hot events.