Twitter Data

Twitter data analysis leverages the vast amount of user-generated content to understand public opinion, behavior, and trends across diverse domains, from weather patterns and financial markets to public health and political events. Current research heavily utilizes natural language processing (NLP) techniques, including transformer-based models like BERT and other deep learning architectures (e.g., LSTM, CNN), along with traditional machine learning algorithms, to perform sentiment analysis, topic modeling, and event detection. This research significantly impacts various fields by providing real-time insights into public sentiment, enabling improved forecasting, risk assessment, and more effective public health interventions and crisis response.