This study investigates how the digital conversation about climate change adapts and evolves when the World Health Organization addresses the health impacts of climate change with different audiences. Drawing on ecolinguistics and Critical Discourse Analysis (CDA) (cf., for instance, Stibbe 2014, 2015; Wang and Huan 2024; Wu 2018; Kinefuchi 2020; Ponton 2022), we analysed the WHO’s six Web platforms, each corresponding to a different continental region, via a Corpus Linguistics (CL) approach augmented by AI and Large Language Models. By leveraging generative pre-trained transformers (GPTs) we aim to detect medical discourse within regional climate change discourse and evaluate its significance and objectives. Our CL-based analysis will be accompanied by a multimodal analysis, in order to identify image similarities and assess how clusters of similar images are used to achieve specific communicative objectives. We will thus determine how the same topic has been adapted discursively to reach diverse audiences residing in distinct geographical, social, and economic contexts, with the goal of encouraging proactive policymaking, raising public awareness, and promoting collective action.
(2025). Climate Change as a Threat to Global Health. The Perspective of the WHO . Retrieved from https://hdl.handle.net/10446/295906
Climate Change as a Threat to Global Health. The Perspective of the WHO
Maci, Stefania Maria;
2025-01-01
Abstract
This study investigates how the digital conversation about climate change adapts and evolves when the World Health Organization addresses the health impacts of climate change with different audiences. Drawing on ecolinguistics and Critical Discourse Analysis (CDA) (cf., for instance, Stibbe 2014, 2015; Wang and Huan 2024; Wu 2018; Kinefuchi 2020; Ponton 2022), we analysed the WHO’s six Web platforms, each corresponding to a different continental region, via a Corpus Linguistics (CL) approach augmented by AI and Large Language Models. By leveraging generative pre-trained transformers (GPTs) we aim to detect medical discourse within regional climate change discourse and evaluate its significance and objectives. Our CL-based analysis will be accompanied by a multimodal analysis, in order to identify image similarities and assess how clusters of similar images are used to achieve specific communicative objectives. We will thus determine how the same topic has been adapted discursively to reach diverse audiences residing in distinct geographical, social, and economic contexts, with the goal of encouraging proactive policymaking, raising public awareness, and promoting collective action.File | Dimensione del file | Formato | |
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