AoIR 2025

Division and Delay in Australian Climate and Energy Discussions: An LLM-Assisted Analysis of Discourse Coalitions across News Reports and Parliamentary Submissions

Carly Lubicz-Zaorski, Katharina Esau, Laura Vodden, Tariq Choucair, Axel Bruns, Michelle Riedlinger, Ehsan Dehghan, and Samantha Vilkins

• 18 Oct. 2025 – Paper presented at the 2025 Association of Internet Researchers conference, Niterói, Rio de Janeiro

Presentation Slides

Abstract

Introduction

Climate action is a divisive topic in many parts of the world, with ongoing debates about issues such as renewable and nuclear energy, carbon taxes, and electric vehicles. Australia’s polarised attitudes to climate change and the stymieing and subversion of climate and energy policy to satisfy the interests of an influential alliance of fossil fuel industry, political, and partisan media actors are well-documented (e.g.,  Chubb, 2012; Crowley, 2021; Holmes & Star, 2018; Stutzer et al., 2021; Taylor, 2014; Wilkinson, 2020). Yet more work is needed to understand the dynamics of these discursive power struggles in contemporary online communication spaces, which are key sites of opinion formation, assertion, and contestation.

Using Large Language Models (LLMs) to study these divisive dynamics at scale, we investigate two distinct communications spaces that influence public and political opinion: (a) mainstream and alternative news media, and (b) public submissions to energy-related Australian Parliamentary Committee inquiries. In each of these arenas, we identify actors, stances, and claims. For news content, we developed a codebook with multiple human coders and used it to train an LLM to classify text published by mainstream and alternative media in Australia. For committee submissions, we worked through an iterative process with an LLM to identify actors, stances, and claims and co-develop a codebook, which we then applied at scale to identify claims in nuclear energy-related public submissions to a recent Australian Parliamentary Committee Inquiry into Nuclear Power Generation in Australia. We then use the actors, stances, and claims in both arenas to map distinct discourse coalitions (Hajer, 1995), revealing patterns of alignment and contestation across multiple discursive sites.

Mainstream and Alternative News Media  

We analyse news content about climate change using a mixed-methods content analysis framework designed to assess polarisation across different dimensions (including ideological, affective, and value-based). To do so, we identify the positions taken and claims made by societal actors appearing in the news articles: for instance, their reported views and statements on renewable energy, fossil fuels, or carbon emissions.

To identify these, we first conduct a standardised manual content analysis of a sample of 350 Australian news articles, to identify key indicators: actors, stances, and claims. The articles were selected through constructed weeks and stratified random sampling, focussing on news coverage surrounding two significant events. The first constructed week spans from 9 November 2023 to 27 December 2023, covering the period around the COP 28 climate summit in Dubai. The second constructed week spans from 19 June 2024 to 6 August 2024, covering debate about the Australian federal opposition’s controversial proposal to introduce nuclear power into the country’s energy mix.  

Building on this manually coded dataset, we then test and train a Large Language Model to extend this content analysis over a larger dataset of climate change news coverage in Australia during 2023 and 2024. Evaluated against our human-coded data, this produces a comprehensive catalogue of societal actors and their stances and claims in relation to climate debates; we further refine and consolidate these results by amalgamating similar claims and grouping actors who represent the same entities.

Parliamentary Submissions  

Having already examined general public debate as covered in news reporting, the second part of our analysis specifically examines 850 public submissions to the 2024 Australian Parliamentary Committee Inquiry into Nuclear Power Generation in Australia. Substantial scholarship has identified overall climate denial claims and (to a lesser extent, due to the complexity involved) policy delay claims and discursive tactics (Coan et al., 2021, Lamb et al., 2020; Martínez Arranz et al., 2024; Painter et al., 2023). But we still need more empirical data on what claims are being made in Australia, and in the context of climate-related policy deliberations. This also needs to consider which actors make what claims, in concert with which allies, and explore what this means for public and political support for climate policy and action.  

Considering the broader socio-political context of these public submissions, we introduce LLM-assisted discourse analysis to classify actors, stances, and claims in the submissions to the Inquiry. We use Claude chat interface to collaboratively develop a codebook of claims that relate to Australia’s nuclear energy debate. This interactive process involves refining a detailed and multi-stage prompt, also providing contextual documents about previous nuclear energy inquiries and a live codebook of claims encountered to date, which is iteratively refined and expanded in response to the ongoing analysis. Once accuracy is established, we then train the LLM to perform the analysis over the entire 850-submission dataset.

Contrary to previous studies’ approaches, this identifies all claims in the documents, not just claims that could be considered obstructive to climate action. This approach responds to the challenge of identifying delay claims, which can be heavily nuanced and context-dependent – what could be a delay claim in one context could be a reasonable argument in other. For example, while established nuclear energy generation may reduce fossil fuel use in some countries, in Australia it cannot be built in time to support the nation’s Net Zero by 2050 target and exploring it as a solution means extending the life of high emissions energy sources like coal (Climate Change Authority, 2025). Further, our identification of all claims also helps to produce results that can be integrated with the results of the news analysis, which similarly captures all actors, stances, and claims relating to climate change and climate policy.  

Assessing Discursive Practices and Discourse Coalitions in News Reporting and Parliamentary Submissions

Finally, we combine the results from the two datasets. By identifying all claims (not only contrarian claims), and focussing on the alignment of actors with each other via these claims, across our analyses of both news media reporting and public submissions to the parliamentary inquiry, we are able to determine who is discursively aligned with or opposed to whom, and how this network of discursive alliances could influence Australian attitudes towards and responses to climate change. In particular, the identification of discourse coalitions across these two communicative spaces highlights potential intersections and divergences between media coverage, political influence, and public engagement in climate discussions.

Through this integrated perspective, this study provides a broader view of climate policy debates in Australia. Aiming to address the nuance and complexity of these debates, we argue that mapping the actors, stances, and claims involved in these debates as ‘discourse coalitions’ (Hajer, 1995; Leifeld, 2017) is particularly useful for analysing nuanced energy transition debates that have technical, economic, scientific, and affective claims, with their validity (i.e., whether they can be deemed obstructive to policy and action or not) very much dependent on country and current context.  

We consider these findings in conjunction with what we already know about the determinants of belief in climate change and support for action (e.g., Colvin et al., 2024; Fielding et al., 2012; Kousser & Tranter, 2018; Pearson et al., 2024; Tranter et al., 2023). In doing so, we aim to inform interventions that can be customised for segments of the Australian population.

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