  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.
