News Dataset

News datasets are collections of news articles used to train and evaluate machine learning models for various tasks, including recommendation, summarization, and misinformation detection. Current research focuses on improving model performance through ensemble methods, addressing issues like news avoidance in recommender systems, and enhancing dataset quality via techniques like LLM-based data cleansing and careful label definition. These advancements are crucial for improving the accuracy and reliability of news-related applications, impacting fields ranging from social science research to financial market forecasting and risk management.