Do fossil fuel firms reframe online climate and sustainability communication? A data-driven analysis
Abstract
Identifying drivers of climate misinformation on social media is crucial to climate action. Misinformation comes in various forms; however, subtler strategies, such as emphasizing favorable interpretations of events or data or reframing conversations to fit preferred narratives, have received little attention. This data-driven paper examines online climate and sustainability communication behavior over 7 years (2014–2021) across three influential stakeholder groups consisting of eight fossil fuel firms (industry), 14 non-governmental organizations (NGOs), and eight inter-governmental organizations (IGOs). We examine historical Twitter interaction data (n = 668,826) using machine learning-driven joint-sentiment topic modeling and vector autoregression to measure online interactions and influences amongst these groups. We report three key findings. First, we find that the stakeholders in our sample are responsive to one another online, especially over topics in their respective areas of domain expertise. Second, the industry is more likely to respond to IGOs' and NGOs' online messaging changes, especially regarding environmental justice and climate action topics. The fossil fuel industry is more likely to discuss public relations, advertising, and corporate sustainability topics. Third, we find that climate change-driven extreme weather events and stock market performance do not significantly affect the patterns of communication among these firms and organizations. In conclusion, we provide a data-driven foundation for understanding the influence of powerful stakeholder groups on shaping the online climate and sustainability information ecosystem around climate change.
Copyright and License
© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Acknowledgement
We thank Michael Ewens for his help accessing the CRSP data we use in this paper. RD's work is supported by the Quadrature Climate Foundation, 2023 Google Cloud Climate Innovation program and the Bill & Melinda Gates Foundation [OPP1144]. KM, TR, and RD acknowledges support from the Cambridge Judge Business School Small Grant Scheme [SG20-09] and Cambridge Faculty of Economics Keynes Fund [JHVH]. RMA and DE's work is supported by Caltech's Resnick Sustainability Institute (DE's work was supported by the Caltech Resnick Sustainability Institute while he was a PhD candidate at Caltech). RD is grateful to Professor Flora Samuel, Stan Finney and Zara Kuckelhaus for supporting with computing infrastructure.
Contributions
These authors contributed equally: Ramit Debnath, Danny Ebanks.
R.D.: Conceptualization, methodology, investigation, data curation, writing—original draft, writing—review & editing, project administration, funding acquisition, supervision. D.E.: Conceptualization, methodology, investigation, formal analysis, data curation, writing—original draft, writing—review & editing, project administration, visualization. K.M.: Conceptualization, funding acquisition. T.R.: Conceptualization, writing—review & editing, funding acquisition. R.M.A.: Conceptualization, methodology, investigation, writing original draft, writing—review & editing, project administration, funding acquisition, supervision.
Data Availability
The materials necessary to reproduce the results reported in this paper are available at https://github.com/danielEban ks/. Energy-Industry-Greenwashing. Per the terms of Twitter's academic use policies, we will make available the tweet IDs for the data used in this paper upon publication. Researchers can obtain the CRSP data from https://www.crsp.org/. Publicly available extreme weather events data can be obtained from EM-DAT (https://www.emdat.be). Alternatively, please contact the corresponding author to request the dataset.
Code Availability
The code necessary to reproduce the results reported in this paper is available at the following GitHub repository: https://github.com/danielEbanks/Energy-Industry-Greenwashing.
Conflict of Interest
The authors declare no competing interests.
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Additional details
- PMCID
- PMC11062293
- Google (United States)
- Bill & Melinda Gates Foundation
- OPP1144
- University of Cambridge
- SG20-09
- University of Cambridge
- Keynes Fund
- Resnick Sustainability Institute
- Caltech groups
- Resnick Sustainability Institute