Twitter Sentiment Analysis Using Deep Learning Algorithms

This study presents a deep learning approach for sentiment analysis on Twitter data. The proposed model classifies tweets into three categories: positive, negative, and neutral. By leveraging neural network architectures, the method effectively captures the semantic and syntactic patterns of social media text. The results demonstrate accurate sentiment detection, providing insights for social media monitoring, opinion analysis, and market research applications.