News is More than a Collection of Facts: Moral Frame Preserving News Summarization
This addresses the need for automated news summarizers to maintain journalists' intent by preserving moral framing, which is important for media consumers and AI ethics, though it is incremental as it builds on existing summarization methods.
The study tackled the problem of preserving moral framing in AI-generated news summaries by proposing an approach that retains morally charged language, demonstrating enhanced preservation while maintaining summary quality through automated, crowd-sourced, and expert evaluations.
News articles are more than collections of facts; they reflect journalists' framing, shaping how events are presented to the audience. One key aspect of framing is the choice to write in (or quote verbatim) morally charged language as opposed to using neutral terms. This moral framing carries implicit judgments that automated news summarizers should recognize and preserve to maintain the original intent of the writer. In this work, we perform the first study on the preservation of moral framing in AI-generated news summaries. We propose an approach that leverages the intuition that journalists intentionally use or report specific moral-laden words, which should be retained in summaries. Through automated, crowd-sourced, and expert evaluations, we demonstrate that our approach enhances the preservation of moral framing while maintaining overall summary quality.