Click the star to add/remove an item to/from your individual schedule.
You need to be logged in to avail of this functionality.
Log in
Accepted Paper:
Paper short abstract:
This paper machine reads the vast scientific literature on climate change. I employ topic modelling to ask, what is the literature about? How has the topic landscape changed? And how can this landscape inform our understanding of the IPCC's relationship with the literature?
Paper long abstract:
The IPCC aims to comprehensively assess the literature on climate change, while balancing legitimacy, relevance and credibility. With 128,000 scientific articles published about climate change since the 5th assessment report in 2013 (compared to just 1,848 before the first assessment report), comprehensive, credible and relevant assessments become ever more challenging. Machine reading this vast corpus offers a way to engage with the literature and understand broad trends at scale. I present a dynamic topic model of over 300,000 abstracts indexed in the Web of Science (WoS). The dynamic topic model identifies fast-growing topics on negative emissions and cities, as well as established topics on atmospheric forcing. By comparing the documents with lists of citations from IPCC reports, I report which topics have been better covered by the IPCC and which topics have received less coverage. This comparison yields evidence to complement the demands made by policy-makers about the IPCC for more solution-oriented knowledge. While topics about the causes and processes of climate change are relatively well represented in IPCC reports, more "solutions-oriented" topics like co2 storage, soil carbon or hydrogen, are less well represented.
What do we still not know about the IPCC?
Session 1