How do news sources tackle controversial issues? In this work, we take a
data-driven approach to understand how controversy interplays with emotional
expression and biased language in the news. We begin by introducing a new
dataset of controversial and non-controversial terms collected using
crowdsourcing. Then, focusing on 15 major U.S. news outlets, we compare
millions of articles discussing controversial and non-controversial issues over
a span of 7 months. We find that in general, when it comes to controversial
issues, the use of negative affect and biased language is prevalent, while the
use of strong emotion is tempered. We also observe many differences across news
sources. Using these findings, we show that we can indicate to what extent an
issue is controversial, by comparing it with other issues in terms of how they
are portrayed across different media.

使用数据驱动方法研究新闻媒体如何处理具有争议性的问题，发现在处理这类问题时通常会出现负面情绪和有偏见的用词，而强烈的情感则会被遏制，同时不同的新闻媒体在处理争议性问题方面存在许多差异。通过这些研究发现，可以比较不同媒体对待争议话题的方式，从而粗略地指示该问题的争议程度。