Twitter Sentiment

Twitter sentiment analysis focuses on understanding the emotional tone expressed in tweets, aiming to quantify public opinion on various topics, from consumer products and political events to financial markets and climate change. Current research employs diverse natural language processing (NLP) techniques, including lexicon-based methods, machine learning algorithms (like Naive Bayes and Random Forests), and deep learning architectures such as CNN-LSTMs and transformers (e.g., Temporal Fusion Transformer), often incorporating multimodal data (text and images) and multilingual capabilities. These analyses provide valuable insights for businesses, policymakers, and researchers, enabling improved market prediction, more effective public health monitoring, and a deeper understanding of societal attitudes towards critical issues.