Controversy and Sentiment in Online News
This work provides insights into media portrayal of controversial issues, which could inform readers and researchers about bias and sentiment in news, though it is incremental as it builds on existing sentiment analysis methods.
The study analyzed how news sources handle controversial issues by comparing emotional expression and biased language in millions of articles from 15 major U.S. outlets over 7 months, finding that controversial topics involve more negative affect and biased language but less strong emotion.
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.