Controversy and Sentiment in Online News
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Sep 2014.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1.
6 papers.
- 2021Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Controlcited by 4
- 2022Anger Breeds Controversy: Analyzing Controversy and Emotions on Redditcited by 3
- 2024Structure and dynamics of growing networks of Reddit threadscited by 2
- 2022Unsupervised Detection of Contextualized Embedding Bias with Application to Ideologycited by 1
- 2023ControversialQA: Exploring Controversy in Question Answeringcited by 1
- 2023Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamicscited by 1
- 2024Structure and dynamics of growing networks of Reddit threads6 Sep 2024
- 2023Exploring Linguistic Style Matching in Online Communities: The Role of Social Context and Conversation Dynamics6 Jul 2023
- 2023ControversialQA: Exploring Controversy in Question Answering10 Feb 2023
- 2022Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology14 Dec 2022
- 2022Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit1 Dec 2022
- 2021Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Control30 Aug 2021