Machine Learning Based Sentiment Analysis of Message on Twitter

Abstract

In the age of information explosion, it is a very important and challenging task to extract the required features from a huge amount of information. The emotion expressed by the text information is one of the most important features of the information. However, there is not much research in this field, so it is of great significance and exploratory to the text sentence emotion analysis. In order to compare and explore better feasibility, both the sequential neural network model and the random forest model were built. Through the contrast between the two models, the machine learning of datasets composed of Twitter comments is carried out to analyze the emotion of the text, and emotion extraction is the research topic of this paper. In this paper, emotion analysis was studied in the order of data processing, model building, and result analysis, and an accuracy of about 90% was finally achieved, which is a good result, from which it can be seen that the constructed neural network model plays a good role.