Ideological biases in social sharing of online information about climate change

ever-increasing volume of online content. Another research question concerns whether the patterns observed on Twitter extend to other online platforms. We studied Twitter due to its prominent role as a means for users to find news stories [55] and its frequent usage as a plat- form for lively political debates in which strangers can interact. If suitable datasets could be obtained, it would be possible to apply similar methods to other popular sites such as Facebook and Reddit; however, privacy restrictions prevent research on many social media platforms. Finally, one further question that is not addressed here is downstream exposure to shared con- tent, that is, who sees the articles that are shared by Twitter users? It is probable that the users captured in our dataset, that select and share online articles about climate change through Twitter, act as ‘opinion leaders’ (following the long-established two-step flow model of Katz and Lazarsfeld [56]), locating new information about the topic and disseminating it to their followers. Measuring the volume of downstream views and retweet rates would answer impor- tant questions about which messages are more effective when shared on social media. One key question is the extent to which polarisation exists in this secondary consumption of climate change media, or whether network effects mitigate polarisation by capturing views from both sides. Any gathering of data from online social networks requires careful consideration of the biases that it may introduce. The users of online platforms are a different distribution of people

than the general population: they tend to be younger, more wealthy and better educated [57]. Our sampling on keywords means that we will capture users who are more engaged with the topic of climate change, and moreover are significantly invested enough to share information with their followers. As such we are considering a highly-motivated sample of a certain part of society, but this is what will be visible to many users when they visit Twitter. This sampling also explains the difference from Global Warming’s Six Americas [1] that we observe, as only the “alarmed” and “dismissive” types are likely to be invested enough to be captured. The work of Williams et al. [18] support this as their coding of Twitter users found only the extreme environmentalists and sceptics. Our keywords were chosen to capture as much of the English language components of the climate change conversation online, but the observed structures may vary in other languages. These factors should be considered in any analysis of social media data but we do not believe that they affect the strength of our findings in any way. This work demonstrates that media communication of information around climate change faces many challenges in the age of social media. Users return to the same trusted sources for information even when presented with new contexts, and any attempts to attract new reader- ships need to consider this behaviour. Understanding how these trusted ties form will be key to combating the spread of misinformation that currently challenges online social networks

and vital for promoting action on climate change and other societal challenges. Supporting information S1 File. (PDF) Author Contributions Conceptualization: Tristan J. B. Cann, Iain S. Weaver. Data curation: Tristan J. B. Cann, Iain S. Weaver. Formal analysis: Tristan J. B. Cann, Iain S. Weaver, Hywel T. P. Williams. Funding acquisition: Hywel T. P. Williams. PLOS ONE Ideological biases in social sharing of online information about climate change PLOS ONE | https://doi.org/10.1371/journal.pone.0250656 April 23, 2021 22 / 25