NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action
Pradip Swarnakar, Ashutosh Modi

TL;DR
This paper explores how NLP techniques can be used to develop a comprehensive knowledge platform that aggregates diverse climate policy data and opinions to support more effective and holistic climate action.
Contribution
It introduces four NLP methodologies for analyzing climate policy discourse and advocates for a knowledge platform integrating varied stakeholder perspectives.
Findings
Automated content analysis identifies key climate policy topics.
Sentiment analysis reveals opinions of major actors on climate issues.
Belief exploration distinguishes pro- and anti-climate orientations.
Abstract
Climate change is a burning issue of our time, with the Sustainable Development Goal (SDG) 13 of the United Nations demanding global climate action. Realizing the urgency, in 2015 in Paris, world leaders signed an agreement committing to taking voluntary action to reduce carbon emissions. However, the scale, magnitude, and climate action processes vary globally, especially between developed and developing countries. Therefore, from parliament to social media, the debates and discussions on climate change gather data from wide-ranging sources essential to the policy design and implementation. The downside is that we do not currently have the mechanisms to pool the worldwide dispersed knowledge emerging from the structured and unstructured data sources. The paper thematically discusses how NLP techniques could be employed in climate policy research and contribute to society's good at…
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Taxonomy
TopicsClimate Change Communication and Perception · Sustainability and Climate Change Governance · Risk Perception and Management
