TWITTER SENTIMENT ANALYSIS

Abstract

Twitter sentiment analysis refers to the process of using natural language processing and machine learning techniques to analyze the sentiment (positive, negative, or neutral) of tweets on Twitter. This analysis can be used to understand public opinion on various topics, such as products, events, and political issues. The sentiment analysis process typically involves data preprocessing, feature extraction, model training, and evaluation. The accuracy of the sentiment analysis model can be improved by using techniques such as word embeddings, sentiment lexicons, and deep learning algorithms. Twitter sentiment analysis has numerous applications, including brand management, customer service, and market research.

Topics & Concepts