IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v55y2021i1d10.1007_s11135-020-00992-w.html
   My bibliography  Save this article

Dynamics and tipping point of issue attention in newspapers: quantitative and qualitative content analysis at sentence level in a longitudinal study using supervised machine learning and big data

Author

Listed:
  • A. E. Opperhuizen

    (Erasmus School of Social and Behavioural Sciences
    Erasmus University Rotterdam)

  • K. Schouten

    (Erasmus School of Social and Behavioural Sciences
    Erasmus University Rotterdam)

Abstract

This study aims to provide a more sensitive understanding of the dynamics and tipping points of issue attention in news media by combining the strengths of quantitative and qualitative research. The topic of this 25-year longitudinal study is the volume and the content of newspaper articles about the emerging risk of gas drilling in The Netherlands. We applied supervised machine learning (SML) because this allowed us to study changes in the quantitative use of subtopics at the detailed sentence level in a large number of articles. The study shows that the actual risk of drilling-induced seismicity gradually increased and that the volume of newspaper attention for the issue also gradually increased for two decades. The sub-topics extracted from media articles during the low media attention period, covering factual information, can be interpreted as a part of episodic frame patterns about the drilling and its consequences. However, a sudden major shift in newspaper attention can be observed in 2013. This sudden disjointed expansion in the volume of media attention on this large-scale technology occurred after a governmental authority classified the drilling-induced earthquakes as a safety issue. After the disjointed issue expansion, safety and decision making were the main subtopics linked to the thematic frames, responsibility, conflict, human interest, and morality. We conclude that SML is a promising tool for future analysis of the growing number of publicly available digitalized textual big datasets, particularly for longitudinal studies and analysis of tipping points and reframing.

Suggested Citation

  • A. E. Opperhuizen & K. Schouten, 2021. "Dynamics and tipping point of issue attention in newspapers: quantitative and qualitative content analysis at sentence level in a longitudinal study using supervised machine learning and big data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(1), pages 19-37, February.
    • Handle: RePEc:spr:qualqt:v:55:y:2021:i:1:d:10.1007_s11135-020-00992-w
    DOI: 10.1007/s11135-020-00992-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-020-00992-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-020-00992-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Charles Vlek, 2018. "Induced Earthquakes from Long‐Term Gas Extraction in Groningen, the Netherlands: Statistical Analysis and Prognosis for Acceptable‐Risk Regulation," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1455-1473, July.
    2. Unknown, 2014. "Media Coverage 2014," 2014: Ethics, Efficiency and Food Security: Feeding the 9 Billion, Well, 26-28 August 2014 225573, Crawford Fund.
    3. Ines Lörcher & Irene Neverla, 2015. "The Dynamics of Issue Attention in Online Communication on Climate Change," Media and Communication, Cogitatio Press, vol. 3(1), pages 17-33.
    4. Jamie K. Wardman & Ragnar Löfstedt, 2018. "Anticipating or Accommodating to Public Concern? Risk Amplification and the Politics of Precaution Reexamined," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1802-1819, September.
    5. Michael Scharkow, 2013. "Thematic content analysis using supervised machine learning: An empirical evaluation using German online news," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 761-773, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chih-Hsing Liu & Jeou-Shyan Horng & Sheng-Fang Chou & Tai-Yi Yu & Yung-Chuan Huang & Jun-You Lin, 2023. "Integrating big data and marketing concepts into tourism, hospitality operations and strategy development," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1905-1922, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olessia Y. Koltsova & Sergei V. Pashakhin, 2017. "Agenda Divergence in a Developing Conflict: A Quantitative Evidence from a Ukrainian and a Russian TV Newsfeeds," HSE Working papers WP BRP 79/SOC/2017, National Research University Higher School of Economics.
    2. Getz, Donald & Page, Stephen J., 2016. "Progress and prospects for event tourism research," Tourism Management, Elsevier, vol. 52(C), pages 593-631.
    3. Oliver Wagner & Thomas Adisorn & Lena Tholen & Dagmar Kiyar, 2020. "Surviving the Energy Transition: Development of a Proposal for Evaluating Sustainable Business Models for Incumbents in Germany’s Electricity Market," Energies, MDPI, vol. 13(3), pages 1-17, February.
    4. Garthwaite, K.A. & Collins, P.J. & Bambra, C., 2015. "Food for thought: An ethnographic study of negotiating ill health and food insecurity in a UK foodbank," Social Science & Medicine, Elsevier, vol. 132(C), pages 38-44.
    5. Mohammad Reyaz, 2020. "Cyberspace in the Post-Soviet States: Assessing the Role of New Media in Central Asia," Jadavpur Journal of International Relations, , vol. 24(1), pages 7-27, June.
    6. Saad, Mohsen & Samet, Anis, 2020. "Collectivism and commonality in liquidity," Journal of Business Research, Elsevier, vol. 116(C), pages 137-162.
    7. Koon-Magnin, Sarah, 2015. "Perceptions of and support for sex offender policies: Testing Levenson, Brannon, Fortney, and Baker’s findings," Journal of Criminal Justice, Elsevier, vol. 43(1), pages 80-88.
    8. Pantea Kamrani & Isabelle Dorsch & Wolfgang G. Stock, 2021. "Do researchers know what the h-index is? And how do they estimate its importance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5489-5508, July.
    9. Afful-Dadzie, Eric & Afful-Dadzie, Anthony, 2017. "Liberation of public data: Exploring central themes in open government data and freedom of information research," International Journal of Information Management, Elsevier, vol. 37(6), pages 664-672.
    10. Jeffrey Cohen & Yuan Ding & Cédric Lesage & Hervé Stolowy, 2017. "Media Bias and the Persistence of the Expectation Gap: An Analysis of Press Articles on Corporate Fraud," Journal of Business Ethics, Springer, vol. 144(3), pages 637-659, September.
    11. Hu, Gang & Jo, Koren M. & Wang, Yi Alex & Xie, Jing, 2018. "Institutional trading and Abel Noser data," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 143-167.
    12. Diana Tsoy & Danijela Godinic & Qingyan Tong & Bojan Obrenovic & Akmal Khudaykulov & Konstantin Kurpayanidi, 2022. "Impact of Social Media, Extended Parallel Process Model (EPPM) on the Intention to Stay at Home during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(12), pages 1-32, June.
    13. Oehler, Andreas & Schmitz, Jonas Tobias, 2021. "Does intensified communication of hedge funds with letters affect abnormal returns?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 127-142.
    14. Yang, Xiaoping & Cao, Dongmei & Andrikopoulos, Panagiotis & Yang, Zonghan & Bass, Tina, 2020. "Online social networks, media supervision and investment efficiency: An empirical examination of Chinese listed firms," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    15. Yang Song, 2020. "The Mismatch Between Mutual Fund Scale and Skill," Journal of Finance, American Finance Association, vol. 75(5), pages 2555-2589, October.
    16. Bai, John (Jianqiu) & Ma, Linlin & Mullally, Kevin A. & Solomon, David H., 2019. "What a difference a (birth) month makes: The relative age effect and fund manager performance," Journal of Financial Economics, Elsevier, vol. 132(1), pages 200-221.
    17. Chen, Yangyang & Goyal, Abhinav & Veeraraghavan, Madhu & Zolotoy, Leon, 2020. "Terrorist attacks, investor sentiment, and the pricing of initial public offerings," Journal of Corporate Finance, Elsevier, vol. 65(C).
    18. Elena Kulchina, 2016. "A path to value creation for foreign entrepreneurs," Strategic Management Journal, Wiley Blackwell, vol. 37(7), pages 1240-1262, July.
    19. Seong Choul Hong, 2020. "Presumed Effects of “Fake News” on the Global Warming Discussion in a Cross-Cultural Context," Sustainability, MDPI, vol. 12(5), pages 1-11, March.
    20. Robert M. Bushman & Christopher D. Williams & Regina Wittenberg‐Moerman, 2017. "The Informational Role of the Media in Private Lending," Journal of Accounting Research, Wiley Blackwell, vol. 55(1), pages 115-152, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:55:y:2021:i:1:d:10.1007_s11135-020-00992-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.