United State Politician

Research on United States politicians is increasingly leveraging computational methods to analyze vast datasets of online political discourse, including social media posts, manifestos, and news transcripts. Current studies focus on identifying and quantifying biases (e.g., gender, ideological) in language used towards and by politicians, employing techniques like sentiment analysis, natural language processing, and machine learning models (e.g., large language models, graph neural networks). These analyses aim to better understand the dynamics of political communication, representation, and the impact of online abuse, informing both political science and the development of more robust online content moderation strategies.