Sentiment Analysis From Machine Learning to Deep Learning
Bolei Chen · 2021 International Conference on Electronic Information Engineering and Computer Science (EIECS) · 2021
Sentiment analysis has been considered as a vital method to analyze a huge amount of documents in digital forms that are widespread and continuously increasing. In general, sentiment analysis plays an important role in social media analysis and business analysis. This paper illustrates sentiment analysis from machine learning methods (TF-IDF, Naïve Bayes, SVM) to deep learning methods (Embedding, LSTM). We explain how the technique developed from sentence level to document level and analyze their advantages and disadvantages.