Public opinion is shaped by the information news media provide, and that
information in turn may be shaped by the ideological preferences of media
outlets. But while much attention has been devoted to media bias via overt
ideological language or topic selection, a more unobtrusive way in which the
media shape opinion is via the strategic inclusion or omission of partisan
events that may support one side or the other. We develop a latent
variable-based framework to predict the ideology of news articles by comparing
multiple articles on the same story and identifying partisan events whose
inclusion or omission reveals ideology. Our experiments first validate the
existence of partisan event selection, and then show that article alignment and
cross-document comparison detect partisan events and article ideology better
than competitive baselines. Our results reveal the high-level form of media
bias, which is present even among mainstream media with strong norms of
objectivity and nonpartisanship. Our codebase and dataset are available at
this https URL

新闻媒体塑造公众舆论，通过选取或省略支持某一方的党派事件以隐晦的方式塑造信息受众的观点，本研究通过比较多篇关于相同事件的新闻文章，并识别出揭示意识形态的党派事件，开发了一种基于潜变量的框架来预测新闻文章的意识形态，发现新闻报道的倾向性可以通过文章之间的对齐和交叉比较获得，相比竞争性基准模型更为准确，结果揭示了媒体的高层次偏见存在，即使是在拥有客观和无党派的强烈规范的主流媒体中也是如此。