Longitudinal Sentiment

Longitudinal sentiment analysis examines how opinions and emotions expressed in text evolve over time, aiming to understand the dynamics of sentiment change across various contexts. Current research utilizes large language models and other machine learning techniques to analyze data from diverse sources like social media and online forums, focusing on challenges like handling code-switching and maintaining classifier accuracy over extended periods. This approach offers valuable insights into societal trends, political discourse, and the spread of misinformation, with applications ranging from monitoring public health crises to understanding radicalization processes.