This study takes Taiwan's political issues as the research theme and uses text analysis to analyze the volume of public opinion. The main purpose of this study is to analyze the volume of public opinion through text analysis, in order to explore whether the volume of public opinion can reflect the factual results in advance, and to understand whether various social media have different subjective positions. This study firstly uses web crawler technology to capture online news related to political issues, and then performs CKIP processing, TF-IDF weight calculation, and establishes a positive and negative public opinion prediction model. The results of the study found that the volume of public opinion can reflect the results of the election in advance, and different social media have their own specific positions. Combined with the analysis of positive and negative public opinion, the positive and negative volume of an event can be predicted.