Ideological biases in social sharing of online information about climate change

RESEARCH ARTICLE Ideological biases in social sharing of online information about climate change Tristan J. B. CannID*, Iain S. Weaver, Hywel T. P. Williams Department of Computer Science, University of Exeter, Exeter, Devon, United Kingdom * tc471@exeter.ac.uk Abstract Exposure to media content is an important component of opinion formation around climate change. Online social media such as Twitter, the focus of this study, provide an avenue to study public engagement and digital media dissemination related to climate change. Shar- ing a link to an online article is an indicator of media engagement. Aggregated link-sharing forms a network structure which maps collective media engagement by the user population. Here we construct bipartite networks linking Twitter users to the web pages they shared, using a dataset of approximately 5.3 million English-language tweets by almost 2 million users during an eventful seven-week period centred on the announcement of the US with- drawal from the Paris Agreement on climate change. Community detection indicates that the observed information-sharing network can be partitioned into two weakly connected components, representing subsets of articles shared by a group of users. We characterise these partitions through analysis of web domains and text content from shared articles, find- ing them to be broadly described as a left-wing/environmentalist group and a right-wing/cli- mate sceptic group. Correlation analysis shows a striking positive association between left/

right political ideology and environmentalist/sceptic climate ideology respectively. Looking at information-sharing over time, there is considerable turnover in the engaged user popula- tion and the articles that are shared, but the web domain sources and polarised network structure are relatively persistent. This study provides evidence that online sharing of news media content related to climate change is both polarised and politicised, with implications for opinion dynamics and public debate around this important societal challenge. Introduction In spite of scientific consensus on the causes and primary effects of climate change, it remains a controversial topic in public and political discourse. Surveys have long shown substantial variation in public beliefs around climate change (for example [1, 2]) and the level of polarisa- tion between individuals supporting and opposing action to mitigate anthropogenic climate change has been growing [3]. Media coverage of climate science and the frames used to present the information can have an important impact on public perceptions and willingness to take action [4], present different motivations and calls for action [5] and influence the accuracy and PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0250656 April 23, 2021 1 / 25 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Cann TJB, Weaver IS, Williams HTP (2021) Ideological biases in social sharing of online information about climate change. PLoS ONE 16(4): e0250656. https://doi.org/10.1371/journal. pone.0250656

Editor: Jarosław Jankowski, West Pomeranian University of Technology, POLAND Received: August 4, 2020 Accepted: April 12, 2021 Published: April 23, 2021 Copyright: © 2021 Cann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The external data used in this study (Twitter posts, news articles) was publicly available when the study was carried out, but since the original data is owned by third parties we cannot publish the complete dataset without infringing Terms of Use (Twitter) or copyright (news articles). Instead we have made available lists of sources (tweet IDs, news article URLs) so that interested parties can reproduce our work. Full details of the dataset and availability are given below. Figshare repository (http://doi.org/10. 6084/m9.figshare.13554590) has been created with the data required to reproduce our results.