774   Insight talk

How Negative Emissions is Framed on Twitter: A Novel Application of Structural Topic Modelling

Negative Emissions (NE) refers to technologies that are capable of taking carbon-dioxide (CO2) out of the atmosphere in order to limit climate change. Due to NE being in its infancy, there have been calls in academia to understand the framing of this concept in order to avoid the same kind of polarisation that climate change has endured. Frames in news-media do not give us an indication of how publics are engaging with and talking about different issues, whereas Twitter presents a stage where individuals can share their own beliefs and attitudes towards new technologies such as NE.

We will present our analysis of these frames on Twitter to highlight how different publics are conceptualising NE. Through a survey, we obtained 10 different keywords which researchers use to communicate NE, and then collected tweets containing these keywords over a three-month period through Twitter API (Nusers = 6,182, Ntweets = 8,524, Period: 10th June – 10th September 2019). Analysis of the tweets will involve Structural Topic Modelling (STM), an automated method of text-analysis, which can not only identify key topics within documents, but also directly estimate the impacts of metadata (e.g. geographical location) on topic prevalence. Twitter users will be coded into discrete groups (e.g. scholars, policy-makers and journalists) to test whether they are framing NE in the same, or different ways.

NE presents a potential pathway to a low carbon future and applying an STM method could be a promising way to gauge public perceptions. Our novel application of STM on a big Twitter dataset will provide insight into whether NE is being talked about, by whom and the different frames characterising it. This presentation will highlight how NE technology development is perceived and discussed, the potential barriers for future development of NE technologies and the subsequent implications for NE stakeholders.

Co-author: Yuanyuan Shang
Australian National University, Australia

Co-author: Nicholas Badullovich
Australian National University, Australia

Return to:   Session parallels: draft program   |   Visual presentations: draft program