Beyond Discrete Genres: Mapping News Items onto a Multidimensional Framework of Genre Cues

Proceedings of the International AAAI Conference on Web and Social Media Pub Date : 2023-06-02 DOI:10.1609/icwsm.v17i1.22167

Zilin Lin, Kasper Welbers, Susan Vermeer, Damian Trilling

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Abstract

In the contemporary media landscape, with the vast and diverse supply of news, it is increasingly challenging to study such an enormous amount of items without a standardized framework. Although attempts have been made to organize and compare news items on the basis of news values, news genres receive little attention, especially the genres in a news consumer’s perception. Yet, perceived news genres serve as an essential component in exploring how news has developed, as well as a precondition for understanding media effects. We approach this concept by conceptualizing and operationalizing a non-discrete framework for mapping news items in terms of genre cues. As a starting point, we propose a preliminary set of dimensions consisting of “factuality” and “formality”. To automatically analyze a large amount of news items, we deliver two computational models for predicting news sentences in terms of the said two dimensions. Such predictions could then be used for locating news items within our framework. This proposed approach that positions news items upon a multidimensional grid helps deepening our insight into the evolving nature of news genres.

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超越离散体裁:将新闻项目映射到体裁线索的多维框架

在当代媒体环境中，由于新闻供应的巨大和多样化，在没有标准化框架的情况下研究如此大量的项目越来越具有挑战性。虽然有人尝试根据新闻价值来组织和比较新闻项目，但新闻类型很少受到关注，特别是新闻消费者感知的类型。然而，感知新闻类型是探索新闻如何发展的重要组成部分，也是理解媒体效应的先决条件。我们通过概念化和操作化一个非离散框架来处理这个概念，该框架用于根据类型线索映射新闻项目。作为出发点，我们提出了一套由“事实性”和“形式性”组成的初步维度。为了自动分析大量的新闻条目，我们提供了两个基于上述两个维度的预测新闻句子的计算模型。这样的预测可以用来在我们的框架内定位新闻项目。这种将新闻项目置于多维网格上的建议方法有助于加深我们对新闻类型演变本质的洞察。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the International AAAI Conference on Web and Social Media

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