Nowadays, big data has played an extremely crucial role in the internet world, applications that involve big data can be seen in different fields like business, entertainment, education, and so on. Thanks to the sufficient study on how to filter, compute and store enormous data, now we can analyze them, make wise decisions, and adopt efficient operations. Natural language processing (NLP) is one of the most popular artificial intelligence application fields in recent years. NLP is the bridge between machine language and human language to achieve the purpose of humancomputer communication. Generally, the textual data is converted into vectors as embedding, then fed into a model for generating a label or another word sequence. Some common tasks like machine translation, text summarization, sentiment analysis, and so on. Sentiment analysis is a fabulous tool in the business industry, it can save us plenty of time, manually distinguishing and labeling texts. This is a summary of the project visualization of tweets’ sentiment analysis. First I Retrieved the sentiment of our dataset through the BERT model, then I made a line chart using HighCharts API. According to the diagram, we can see fewer people were afraid of vaccination, more people felt angry from September 2021 to October 2021.