Abstract
Narratives serve as fundamental frameworks in our understanding of the world and play a crucial role in collaborative sensemaking, providing a versatile foundation for sensemaking. Framing is a subtle yet potent mechanism that influences public perception through specific word choices, shaping interpretations of reported news events. Despite the recognized importance of narratives and framing, a significant gap exists in the literature with regard to the explicit consideration of framing within the context of computational extraction and representation. This article explores the capabilities of a specific narrative extraction and representation approach -- narrative maps -- to capture framing information from news data. The research addresses two key questions: (1) Does the narrative extraction method capture the framing distribution of the data set? (2) Does it produce a representation with consistent framing? Our results indicate that while the algorithm captures framing distributions, achieving consistent framing across various starting and ending events poses challenges. Our results highlight the potential of narrative maps to provide users with insights into the intricate framing dynamics within news narratives. However, we note that directly leveraging framing information in the computational narrative extraction process remains an open challenge.
Abstract (translated)
叙述在我们的对世界的理解中扮演着基本框架的角色，并且在协作意义理解中发挥着关键作用，为意义理解提供了一个多功能的基础。框架是一种微妙而强大的机制，通过特定的词汇选择影响公众的看法，塑造了对报道的新闻事件的理解。尽管叙述和框架在文献中被认为是重要的，但在计算提取和表示的背景下对框架的明确考虑仍然存在很大的空白。本文探讨了特定叙事提取和表示方法——故事地图——从新闻数据中捕捉框架信息的能力。研究解决了两个关键问题：（1）叙事提取方法是否捕捉到了数据集的框架分布？（2）它是否产生了具有一致框架的表示？我们的结果表明，虽然算法捕捉到了框架分布，但在各种开始和结束事件之间实现一致的框架仍然具有挑战性。我们的结果强调了故事地图为用户提供了深入了解新闻叙述中复杂的框架动态的潜力。然而，我们指出，在计算叙述提取过程中直接利用框架信息仍然是一个开放挑战。
URL
https://arxiv.org/abs/2405.02677
