Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding U.S. Gun Violence
Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding U.S. Gun Violence
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DOI：
10.18653/v1/k19-1047
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
Siyi Liu;Lei Guo;Kate K. Mays;Margrit Betke;D. Wijaya
中科院分区：
文献类型：
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作者：
Siyi Liu;Lei Guo;Kate K. Mays;Margrit Betke;D. Wijaya
关于同一话题的不同新闻文章往往会提供不同的观点：一篇关于枪支暴力的文章可能会强调枪支管制，而另一篇可能会宣传第二修正案的权利，而第三篇可能会关注心理健康问题。在传播学研究中，这些不同的视角被称为“框架”，当新闻媒体使用这些框架时，它们会以多种方式影响读者的意见。本文提出了一种有效检测新闻标题帧的方法。我们的培训和绩效评估是基于与美国枪支暴力问题相关的新闻标题的新数据集。这个枪支暴力框架语料库（GVFC）由新闻和传播专家策划和注释。我们提出的方法为多类新闻帧检测设置了新的最先进的性能，在精度上明显优于最近的基线35.9%的绝对差异。我们将帧检测方法应用于对2016年至2018年美国有关枪支暴力报道的8.8万条新闻头条的大规模研究。
Different news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, and yet a third might focus on mental health issues. In communication research, these different perspectives are known as “frames”, which, when used in news media will influence the opinion of their readers in multiple ways. In this paper, we present a method for effectively detecting frames in news headlines. Our training and performance evaluation is based on a new dataset of news headlines related to the issue of gun violence in the United States. This Gun Violence Frame Corpus (GVFC) was curated and annotated by journalism and communication experts. Our proposed approach sets a new state-of-the-art performance for multiclass news frame detection, significantly outperforming a recent baseline by 35.9% absolute difference in accuracy. We apply our frame detection approach in a large scale study of 88k news headlines about the coverage of gun violence in the U.S. between 2016 and 2018.