Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 17, 2022 | Published + Supplemental Material
Journal Article Open

Social media enables people-centric climate action in the hard-to-decarbonise building sector

Abstract

The building and construction sector accounts for around 39% of global carbon dioxide emissions and remains a hard-to-abate sector. We use a data-driven analysis of global high-level climate action on emissions reduction in the building sector using 256,717 English-language tweets across a 13-year time frame (2009–2021). Using natural language processing and network analysis, we show that public sentiments and emotions on social media are reactive to these climate policy actions. Between 2009–2012, discussions around green building-led emission reduction efforts were highly influential in shaping the online public perceptions of climate action. From 2013 to 2016, communication around low-carbon construction and energy efficiency significantly influenced the online narrative. More significant interactions on net-zero transition, climate tech, circular economy, mass timber housing and climate justice in 2017–2021 shaped the online climate action discourse. We find positive sentiments are more prominent and recurrent and comprise a larger share of the social media conversation. However, we also see a rise in negative sentiment by 30–40% following popular policy events like the IPCC report launches, the Paris Agreement and the EU Green Deal. With greater online engagement and information diffusion, social and environmental justice topics emerge in the online discourse. Continuing such shifts in online climate discourse is pivotal to a more just and people-centric transition in such hard-to-decarbonise sectors.

Additional Information

© The Author(s) 2022. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. RD acknowledges support from the Cambridge Zero and Quadrature Climate Foundation, Laudes Foundation, the Bill and Melinda Gates Foundation [OPP1144], Cambridge Judge Business School Small Grant (2020–21), the Keynes Fund 2021–22 [JHVH] and the Alan Turing Institute's Postdoctoral Enrichment Award [G116750]. Caltech's Resnick Sustainability Institute supports RMA's work. RB's work is supported by the UK Space Agency NSIP Award (2021–22). We would also like to thank Twitter for providing access to their APIs. A working paper version of this study can be found at Cambridge Working Paper in Economics 2202. Data availability. The datasets analysed during the current study are available in the Open Science Framework repository https://doi.org/10.17605/OSF.IO/QC453. The user identifiers are anonymized as per Twitter's developers policy and GDPR rules https://gdpr.twitter.com/see here. Ethics approval. This research was reviewed by the Institutional Review Board at the Judge Business School, University of Cambridge (20-064) and at the California Institute of Technology (21-1169). Twitter was informed about this research during the v2API request.

Attached Files

Published - 41598_2022_Article_23624.pdf

Supplemental Material - 41598_2022_23624_MOESM1_ESM.pdf

Files

41598_2022_Article_23624.pdf
Files (11.4 MB)
Name Size Download all
md5:8b5c83bebf4917a226edb7da6525fa79
7.6 MB Preview Download
md5:9f90a54ca5068aad87e64aea2931574d
3.8 MB Preview Download

Additional details

Created:
August 22, 2023
Modified:
October 23, 2023