Identifying biases in news using models of narrative framing

使用叙事框架模型识别新闻偏见

• 批准号: DE230100761
• 负责人: Dr Lea Frermann
• 金额: $ 30.31万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE230100761
• 关键词: Identifying; biases; news; using; models

This project aims to develop tools to detect biased narratives and one-sided framing in news stories using novel natural language processing methods to understand the text more deeply. Unlike existing methods, which overly rely on surface word co-occurrences patterns, the novel methods will be able to capture narratives in a more holistic and intuitive manner. Expected outcomes include new modeling techniques grounded in theory and a tool to highlight biases with recommendations for diverse sets of news articles. By raising awareness to biased news reporting, the project will benefit Australians through more balanced public discourse on global challenges, such as climate change and health pandemics.

该项目旨在开发工具，以使用新颖的自然语言处理方法来检测新闻故事中有偏见的叙述和单方面的框架，以更深入地理解文本。与现有的方法（过度依赖于表面词共发生模式）不同，这种新方法将能够以更全面和直观的方式捕捉叙事。预期的结果包括以理论为基础的新建模技术，以及一种强调各种新闻文章的建议的工具。通过提高人们对偏见的新闻报道的认识，该项目将通过对全球挑战（例如气候变化和健康大流行病）进行更平衡的公众讨论来使澳大利亚人受益。