论文标题
写了什么与谁阅读：新闻媒体使用文本分析和社交媒体环境进行分析
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context
论文作者
论文摘要
预测整个新闻媒体报告的政治偏见和事实是媒体分析的关键要素，这是一个研究的，但越来越重要的研究方向。在线伪造，有偏见和宣传内容的当前级别使事实检查每个可疑主张，无论是手动或自动的。另外，我们可以介绍整个新闻媒体，并寻找可能发布假或有偏见的内容的新闻媒体。这种方法可以通过简单地检查其来源的可靠性来检测其发布时可能的“假新闻”即可。从实际的角度来看，报告的政治偏见和事实具有语言方面，但也具有社会背景。在这里，我们研究两者的影响，即（i）所写的内容（即目标介质发表的内容，以及它在Twitter上的描述）与（ii）阅读（即分析Facebook，Twitter和Twitter和YouTube上的目标介质的读者）。我们进一步研究Wikipedia上有关目标介质的文章。评估结果表明，书面最重要的是，将所有信息源放在一起，对当前的最新作品产生了巨大的改进。
Predicting the political bias and the factuality of reporting of entire news outlets are critical elements of media profiling, which is an understudied but an increasingly important research direction. The present level of proliferation of fake, biased, and propagandistic content online, has made it impossible to fact-check every single suspicious claim, either manually or automatically. Alternatively, we can profile entire news outlets and look for those that are likely to publish fake or biased content. This approach makes it possible to detect likely "fake news" the moment they are published, by simply checking the reliability of their source. From a practical perspective, political bias and factuality of reporting have a linguistic aspect but also a social context. Here, we study the impact of both, namely (i) what was written (i.e., what was published by the target medium, and how it describes itself on Twitter) vs. (ii) who read it (i.e., analyzing the readers of the target medium on Facebook, Twitter, and YouTube). We further study (iii) what was written about the target medium on Wikipedia. The evaluation results show that what was written matters most, and that putting all information sources together yields huge improvements over the current state-of-the-art.
