Research on public opinion analysis based on TF-IDF algorithm—Taking Japan's nuclear wastewater discharge incident as an example
The incident of Japan's nuclear wastewater discharge to the sea has caused great repercussions on the Internet.It has rapidly expanded and spread to many aspects of society,forming a public opinion event,which has affected social management and even social stability to a certain extent.It can be seen that timely capture of online public opinion,analysis of its characteris-tics,and relevant functional departments taking preventive measures based on this have become urgent problems to be solved.A public opinion monitoring program based on TF-IDF and Word2Vec algorithm has been developed to meet this demand.Firstly,the Weibo content text is cleaned and segmented,and then the TF-IDF algorithm is used to extract Weibo text keywords.Secondly,the keywords are sorted by weight and a word cloud map is generated.Finally,the words are converted into high-dimensional vec-tors and visualized on a two-dimensional plane,providing decision-making basis for public opinion monitoring.
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