Sentiment Analysis And Clustering Research On Sina Weibo User Comments

With the progress of Internet technology,WeChat,QQ,weibo and other network information release platforms have been further developed.On the Internet,the platform and technology for information release and access have been greatly developed.Weibo,WeChat and other new network platforms have gradually become more mainstream information exchange platforms.In recent years,sina weibo,as the main outbreak source and communication channel of emergencies and hot topics,has become the main driving force of collecting public opinions on social networks.Weibo comments are a collection of different attitudes of the public towards hot issues.How to widely collect opinions and observe the public situation has become the main research direction of analyzing microblog comment data.Structured,semi-structured and unstructured data constitute a large amount of data stored in sina weibo and other network platforms.Unstructured data accounts for a large proportion,and in the unstructured data,most of the text data.Obtaining useful information from network information has become a hot topic in academic and business circles.This paper first carried out the relevant research work based on sina weibo user comments.Firstly,the characteristics of sina weibo user comments were analyzed,and then the theoretical knowledge and technology related to the research in this paper were summarized.Then,the research on the sentiment analysis of weibo comments based on machine learning was conducted,followed by the clustering research on user comments.Sina weibo comment data collected by web crawlers were used as experimental samples for verification,and the results were evaluated.Finally,the practical application of sina weibo user comment mining and analysis in social management decisions was studied.