Political Discourse

Political discourse analysis utilizes computational linguistics to understand the nuances of political communication across various platforms, aiming to uncover patterns in sentiment, ideology, and the spread of misinformation. Current research leverages large language models (LLMs), particularly transformer-based architectures, for tasks like stance detection, sentiment analysis, and speaker attribution, often employing zero-shot or few-shot learning techniques to minimize annotation costs. These advancements enable efficient analysis of large corpora of political text, offering insights into political polarization, the impact of fake news, and the effectiveness of political rhetoric, with implications for both social science research and practical applications like content moderation.