Fifty Shades of Greenwashing: The Political Economy of Climate Change Advertising on Social Media
- URL: http://arxiv.org/abs/2511.14930v1
- Date: Tue, 18 Nov 2025 21:32:19 GMT
- Title: Fifty Shades of Greenwashing: The Political Economy of Climate Change Advertising on Social Media
- Abstract summary: We show how polluting companies can use social media advertising related to climate change to redirect criticism.<n>We identify greenwashing content in 11 million social-political ads in Meta's Ad Targeting Datset.<n>We show that much of this advertising happens via organizations with undisclosed links to the fossil fuel industry.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we provide a novel measure for greenwashing -- i.e., climate-related misinformation -- that shows how polluting companies can use social media advertising related to climate change to redirect criticism. To do so, we identify greenwashing content in 11 million social-political ads in Meta's Ad Targeting Datset with a measurement technique that combines large language models, human coders, and advances in Bayesian item response theory. We show that what is called greenwashing has diverse actors and components, but we also identify a very pernicious form, which we call political greenwashing, that appears to be promoted by fossil fuel companies and related interest groups. Based on ad targeting data, we show that much of this advertising happens via organizations with undisclosed links to the fossil fuel industry. Furthermore, we show that greenwashing ad content is being micro-targeted at left-leaning communities with fossil fuel assets, though we also find comparatively little evidence of ad targeting aimed at influencing public opinion at the national level.
Related papers
- A Multimodal Benchmark for Framing of Oil & Gas Advertising and Potential Greenwashing Detection [36.01013743439459]
We introduce a benchmark dataset of expert-annotated video ads from Facebook and YouTube.<n>The dataset provides annotations for 13 framing types for more than 50 companies or advocacy groups across 20 countries.<n>Our dataset contributes to research in multimodal analysis of strategic communication in the energy sector.
arXiv Detail & Related papers (2025-10-24T17:34:28Z) - Latent Topic Synthesis: Leveraging LLMs for Electoral Ad Analysis [51.95395936342771]
We introduce an end-to-end framework for automatically generating an interpretable topic taxonomy from an unlabeled corpus.<n>We apply this framework to a large corpus of Meta political ads from the month ahead of the 2024 U.S. Presidential election.<n>Our approach uncovers latent discourse structures, synthesizes semantically rich topic labels, and annotates topics with moral framing dimensions.
arXiv Detail & Related papers (2025-10-16T20:30:20Z) - Corporate Greenwashing Detection in Text - a Survey [5.958302080525902]
Greenwashing is an effort to mislead the public about the environmental impact of an entity, such as a state or company.<n>We provide a comprehensive survey of the scientific literature addressing natural language processing methods to identify greenwashing.
arXiv Detail & Related papers (2025-02-11T13:28:56Z) - On the Use of Proxies in Political Ad Targeting [49.61009579554272]
We show that major political advertisers circumvented mitigations by targeting proxy attributes.
Our findings have crucial implications for the ongoing discussion on the regulation of political advertising.
arXiv Detail & Related papers (2024-10-18T17:15:13Z) - Understanding Environmental Posts: Sentiment and Emotion Analysis of
Social Media Data [0.0]
This study analyzes the public perception of climate change and the environment over a decade from 2014 to 2023.
Negative environmental tweets are far more common than positive or neutral ones.
The most common emotions in environmental tweets are fear, trust, and anticipation.
arXiv Detail & Related papers (2023-12-05T19:26:28Z) - Analysis of Climate Campaigns on Social Media using Bayesian Model
Averaging [29.413444722550356]
We analyze how industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change.
We propose a minimally supervised model soup [57] approach combined with messaging themes to identify the stances of climate ads on Facebook.
arXiv Detail & Related papers (2023-05-06T16:43:29Z) - How Do US Congress Members Advertise Climate Change: An Analysis Of Ads
Run On Meta's Platforms [0.0]
We use Meta's Ad Library to collect 602,546 ads that have been issued by US Congress members since mid-2018.
We find that Democrats focus substantially more on climate change than Republicans, with 99.7% of all climate-related ads stemming from Democratic politicians.
Republicans generate on average 188% more impressions with their climate ads for the same money spent as Democrats.
arXiv Detail & Related papers (2023-04-06T17:58:41Z) - Climate Change & Computer Audition: A Call to Action and Overview on
Audio Intelligence to Help Save the Planet [98.97255654573662]
This work provides an overview of areas in which audio intelligence can contribute to overcome climate-related challenges.
We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether.
arXiv Detail & Related papers (2022-03-10T13:32:31Z) - Reaching the bubble may not be enough: news media role in online
political polarization [58.720142291102135]
A way of reducing polarization would be by distributing cross-partisan news among individuals with distinct political orientations.
This study investigates whether this holds in the context of nationwide elections in Brazil and Canada.
arXiv Detail & Related papers (2021-09-18T11:34:04Z) - News consumption and social media regulations policy [70.31753171707005]
We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation.
Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content.
The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
arXiv Detail & Related papers (2021-06-07T19:26:32Z) - Analyzing Sustainability Reports Using Natural Language Processing [68.8204255655161]
In recent years, companies have increasingly been aiming to both mitigate their environmental impact and adapt to the changing climate context.
This is reported via increasingly exhaustive reports, which cover many types of climate risks and exposures under the umbrella of Environmental, Social, and Governance (ESG)
We present this tool and the methodology that we used to develop it in the present article.
arXiv Detail & Related papers (2020-11-03T21:22:42Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.