Estimating Ideal Points of Newspapers from Editorial Texts
Estimating Ideal Points of Newspapers from Editorial Texts
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DOI：
10.1177/1940161220935058
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发表时间：
2020-07-10
影响因子：
4.8
通讯作者：
Miwa, Hirofumi
中科院分区：
文献类型：
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作者：
Kaneko, Tomoki;Asano, Taka-aki;Miwa, Hirofumi
虽然测量新闻媒体的理想点是检验基于空间理论的政治传播理论的关键，但以往的媒体理想点估计方法存在各种缺陷，包括时间和人力资源成本高，对不同国家的适用性低。我们提出，文本数据的无监督机器学习技术，特别是文本缩放方法和潜在话题建模的结合，可以用于估计媒体的理想点。我们将我们提出的方法应用于日本十家国家和地区报纸的编辑文本，以前的方法不适用，因为报纸从未正式批准过特定的政党或候选人，而且没有用于监督学习的高质量培训数据。我们的两项研究，一项分析了单一典型意识形态主题的社论，另一项调查了目标报纸在一年内发表的所有社论，证实了日本报纸意识形态倾向的普遍观点，这验证了我们所提出的方法的有效性。我们还说明，我们的方法允许学者调查哪些问题与媒体各自的意识形态立场密切相关。此外，我们使用报纸的估计理想点来表明，日本人部分倾向于阅读意识形态相似的报纸，并关注此类报纸的Twitter账户，尽管这些报纸的倾向性并不明显。
Although measuring the ideal points of news media is essential for testing political communication theories based on spatial theory, prior methods of estimating ideal points of media outlets have various shortcomings, including high cost in terms of time and human resources and low applicability to different countries. We propose that unsupervised machine learning techniques for text data, specifically the combination of a text scaling method and latent topic modeling, can be applied to estimate ideal points of media outlets. We applied our proposed methods to editorial texts of ten national and regional newspapers in Japan, where prior approaches are not applicable because newspapers have never officially endorsed particular parties or candidates, and because high-quality training data for supervised learning are not available. Our two studies, one of which analyzed editorials on a single typically ideological topic while the other investigated all editorials published by the target papers in one year, confirmed the popular view of Japanese newspapers' ideological slant, which validates the effectiveness of our proposed approach. We also illustrate that our methods allow scholars to investigate which issues are closely related to the respective ideological positions of media outlets. Furthermore, we use the estimated ideal points of newspapers to show that Japanese people partially tend to read ideologically like-minded newspapers and follow such newspapers' Twitter accounts even though their slant is not explicit.