Journalistic Type News

Research on journalistic-type news is increasingly focused on understanding and mitigating biases in news production and consumption, particularly in the context of online platforms and the rise of generative AI. Current studies utilize machine learning techniques, including natural language processing and various classification algorithms (e.g., logistic regression, support vector machines), to analyze news content, detect fake news, and assess the impact of algorithmic ranking and AI-generated articles on news framing and representation of diverse voices. This work aims to improve news accuracy, fairness, and inclusivity, offering valuable tools for journalists and researchers alike to enhance the quality and trustworthiness of news reporting.