Understanding how online media frame issues is crucial due to their impact on public opinion. Research on framing using natural language processing techniques mainly focuses on specific content features in messages and neglects their narrative elements. Also, the distinction between framing in different sources remains an understudied problem. We address those issues and investigate how the framing of health-related topics, such as COVID-19 and other diseases, differs between conspiracy and mainstream websites. We incorporate narrative information into the framing analysis by introducing a novel frame extraction approach based on semantic graphs. We find that health-related narratives in conspiracy media are predominantly framed in terms of beliefs, while mainstream media tend to present them in terms of science. We hope our work offers new ways for a more nuanced frame analysis.

翻译：理解网络媒体如何构建议题框架至关重要，因其对公众舆论具有深远影响。基于自然语言处理技术的框架分析研究主要聚焦于信息中的特定内容特征，而忽略了其叙事要素。同时，不同来源间的框架差异仍是一个研究不足的问题。我们针对这些难题展开研究，探讨阴谋论网站与主流网站如何以不同框架呈现健康相关议题（如新冠肺炎及其他疾病）。我们通过引入一种基于语义图的新型框架提取方法，将叙事信息纳入框架分析之中。研究发现，阴谋论媒体中的健康叙事主要以信念框架呈现，而主流媒体则倾向于以科学框架加以呈现。我们期望本研究能为更精细的框架分析提供新路径。