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Thesis

What is known about climate change? A knowledge graph approach

Abstract:
The latest findings from the Intergovernmental Panel on Climate Change Sixth Assessment Report retells a story already told in 1979 in greater detail --- that climate change is happening because of human causes. However, the progress on addressing the climate crisis hardly corresponds to the media's nearly 40 years of news coverage. A widely cited barrier to progress is the lack of knowledge to comprehend the various interacting aspects of climate change. As a dynamic complex system, climate change is a deeply relational systems-level problem that requires communication and mental models capable of communicating system complexities. To establish the extent of relations and knowledge formations by past communications, this paper offers a methodological innovation enabling network analysis of unstructured texts. This research developed a reproducible automated semantic network approach using natural language processing and open information extraction tools to construct knowledge graphs (KGs) on climate change news coverage in 5 countries using news articles $(N = 19,684)$ from 1990 to 2020. Country comparisons were carried out cross-sectionally and longitudinally. The findings show that the KGs are structurally similar while static but differed substantially in longitudinal patterns. Countries performing better in climate commitments saw a uniform increase in the salience and embedded of concepts, while in those less progressive countries, concepts become salient sporadically. The study concludes by recommending a concerted communication model that gives equal and parallel issue-attention to the causal, action, and physical characteristic and consequence frames of climate change to facilitate understanding of the system complexity of climate change.

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Division:
SSD
Department:
Oxford Internet Institute
Sub department:
Oxford Internet Institute
Oxford college:
Linacre College
Role:
Author
ORCID:
0000-0002-7042-1025

Contributors

Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Sub department:
Oxford Internet Institute
Role:
Supervisor
ORCID:
0000-0002-5444-2280
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Sub department:
Oxford Internet Institute
Role:
Supervisor
ORCID:
0000-0002-6894-4951


DOI:
Type of award:
MSc
Level of award:
Masters
Awarding institution:
University of Oxford

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