Political Sentiment

Political sentiment analysis aims to understand and quantify public opinion on political issues, leveraging computational methods to analyze textual data from various sources like social media and news articles. Current research focuses on improving the accuracy and fairness of sentiment classification using large language models (LLMs) and other machine learning techniques, while also investigating biases and limitations in these models, particularly concerning their potential for political skew and the influence of factors like gender and occupation. This field is crucial for understanding political polarization, informing political strategies, and mitigating the spread of misinformation, with implications for both social science research and the development of more responsible AI systems.