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Negativity drives online news consumption

Author

Listed:
  • Claire E. Robertson

    (New York University)

  • Nicolas Pröllochs

    (University of Giessen)

  • Kaoru Schwarzenegger

    (ETH Zurich)

  • Philip Pärnamets

    (Karolinska Institutet)

  • Jay J. Bavel

    (New York University
    New York University)

  • Stefan Feuerriegel

    (ETH Zurich
    LMU Munich)

Abstract

Online media is important for society in informing and shaping opinions, hence raising the question of what drives online news consumption. Here we analyse the causal effect of negative and emotional words on news consumption using a large online dataset of viral news stories. Specifically, we conducted our analyses using a series of randomized controlled trials (N = 22,743). Our dataset comprises ~105,000 different variations of news stories from Upworthy.com that generated ∼5.7 million clicks across more than 370 million overall impressions. Although positive words were slightly more prevalent than negative words, we found that negative words in news headlines increased consumption rates (and positive words decreased consumption rates). For a headline of average length, each additional negative word increased the click-through rate by 2.3%. Our results contribute to a better understanding of why users engage with online media.

Suggested Citation

  • Claire E. Robertson & Nicolas Pröllochs & Kaoru Schwarzenegger & Philip Pärnamets & Jay J. Bavel & Stefan Feuerriegel, 2023. "Negativity drives online news consumption," Nature Human Behaviour, Nature, vol. 7(5), pages 812-822, May.
  • Handle: RePEc:nat:nathum:v:7:y:2023:i:5:d:10.1038_s41562-023-01538-4
    DOI: 10.1038/s41562-023-01538-4
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    References listed on IDEAS

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    1. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
    2. M. J. Crockett, 2017. "Moral outrage in the digital age," Nature Human Behaviour, Nature, vol. 1(11), pages 769-771, November.
    3. Fabiana Zollo & Petra Kralj Novak & Michela Del Vicario & Alessandro Bessi & Igor Mozetič & Antonio Scala & Guido Caldarelli & Walter Quattrociocchi, 2015. "Emotional Dynamics in the Age of Misinformation," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-22, September.
    4. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    5. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    6. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    7. Stuart Soroka & Patrick Fournier & Lilach Nir, 2019. "Cross-national evidence of a negativity bias in psychophysiological reactions to news," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(38), pages 18888-18892, September.
    8. Stuart Soroka & Lori Young & Meital Balmas, 2015. "Bad News or Mad News? Sentiment Scoring of Negativity, Fear, and Anger in News Content," The ANNALS of the American Academy of Political and Social Science, , vol. 659(1), pages 108-121, May.
    9. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    10. Malte Toetzke & Nicolas Banholzer & Stefan Feuerriegel, 2022. "Monitoring global development aid with machine learning," Nature Sustainability, Nature, vol. 5(6), pages 533-541, June.
    11. Khalilzadeh, Jalayer & Tasci, Asli D.A., 2017. "Large sample size, significance level, and the effect size: Solutions to perils of using big data for academic research," Tourism Management, Elsevier, vol. 62(C), pages 89-96.
    12. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
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    Cited by:

    1. Fève, Patrick & Assenza, Tiziana & Collard, Fabrice & Huber, Stefanie, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," TSE Working Papers 24-1516, Toulouse School of Economics (TSE).
    2. Shuhuan Zhou & Xiaokun Yang & Yi Wang & Xia Zheng & Zhian Zhang, 2023. "Affective agenda dynamics on social media: interactions of emotional content posted by the public, government, and media during the COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    3. Ximeng Fang & Sven Heuser & Lasse S. Stötzer, 2023. "How In-Person Conversations Shape Political Polarization: Quasi-Experimental Evidence from a Nationwide Initiative," ECONtribute Discussion Papers Series 270, University of Bonn and University of Cologne, Germany.

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