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Media Framing through the Lens of Event-Centric Narratives
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From a communications perspective, a frame defines the packaging of the language used in such a way as to encourage certain interpretations and to discourage others. For example, a news article can frame immigration as either a boost or a drain on the economy, and thus communicate very different interpretations of the same phenomenon. In this work, we argue that to explain framing devices we have to look at the way narratives are constructed. As a first step in this direction, we propose a framework that extracts events and their relations to other events, and groups them into high-level narratives that help explain frames in news articles. We show that our framework can be used to analyze framing in U.S. news for two different domains: immigration and gun control.
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MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media
MGM augments graph neural networks with globally similar media nodes and language model probabilities, improving factuality and bias classification of news outlets.
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