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Research on Public Sentiment of Weibo Topics Based on Emotional Tendency-Taking “LaBiXiaoQiu Was Detained” as an Example

With the booming development of social media, many people use social software to share their life experiences and express their opinions, viewpoints and experiences on social hot spots, thus forming a huge amount of information. This paper takes microblog topic comments as the research object and makes visual analysis of microblog comments from the perspective of emotional orientation, which is of great research significance for relevant departments to timely grasp the changes in the masses' thoughts and timely control and deal with emergencies. In this study, the Bert-LSTM model was used for sentiment classification of microblog comments, and the complex and sparse data sets were visualized to convert the disordered data signals into graphic representations. Through in-depth emotional mining of public opinion comments, the importance and effectiveness of online public opinion analysis in the era of data explosion are verified.