- Title
- United in criticism: The discursive politics and coalitions of Australian energy debates on social media
- Creator
- Martínez Arranz, Alfonso; Askland, Hedda Haugen; Box, Yasmin; Scurr, Ivy
- Relation
- Energy Research and Social Science Vol. 108, Issue February 2024, no. 102591
- Publisher Link
- http://dx.doi.org/10.1016/j.erss.2022.102591
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2024
- Description
- This paper applies social network analysis (SNA) and natural language processing (NLP) tools within a traditional discourse analysis framework to better understand the polarisation in the online debate around climate and energy issues. We draw on tweets over 2019–2021 to characterise a large network of over 10,000 highly followed Twitter users that participate in the Australian climate and energy debate on this social media platform. Through community detection algorithms, we identify five “discourse coalitions”. Drawing on quantitative analysis of hashtags and mentions, topic modelling of their tweets, and identifying the most central users, we characterise four as anti-coal and one as anti-renewables. The former focus on current affairs, grassroots activism, science and technology, and Green politics, while the latter is made up by conservative commentators, including climate change deniers, who emphasise coal as a valuable commodity. A bipolar distribution of opinions is thus easy to discern, but the widespread picture of “echo chambers” seems inaccurate, since there is significant exchange and interconnection between opposing poles. Another distinct finding is that the debate, albeit civil compared to results from other studies, is focused on criticism and outrage. Those opposed to renewables talked more about wind power than those pro-renewables, and coal opponents spoke mostly about coal. Technological choices with ambiguous positioning, e.g., carbon capture and storage, were ignored across all coalitions. Giving neutral or positive themes greater circulation appears desirable but may require much more interventionism than Twitter and other social media are prepared to undertake.
- Subject
- coal; community detection; topic modelling; discourse analysis
- Identifier
- http://hdl.handle.net/1959.13/1499509
- Identifier
- uon:54703
- Identifier
- ISSN:2214-6296
- Language
- eng
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