NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action

• URL: http://arxiv.org/abs/2105.05621v1
• Date: Wed, 12 May 2021 12:30:02 GMT
• Title: NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action
• Authors: Pradip Swarnakar and Ashutosh Modi
• Abstract summary: The paper thematically discusses how NLP techniques could be employed in climate policy research. We exemplify symbiosis of NLP and Climate Policy Research via four methodologies. The present theme paper further argues that creating a knowledge platform would help in the formulation of a holistic climate policy.
• Score: 2.482368922343792
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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 large. In particular, we exemplify symbiosis of NLP and Climate Policy Research via four methodologies. The first one deals with the major topics related to climate policy using automated content analysis. We investigate the opinions (sentiments) of major actors' narratives towards climate policy in the second methodology. The third technique explores the climate actors' beliefs towards pro or anti-climate orientation. Finally, we discuss developing a Climate Knowledge Graph. The present theme paper further argues that creating a knowledge platform would help in the formulation of a holistic climate policy and effective climate action. Such a knowledge platform would integrate the policy actors' varied opinions from different social sectors like government, business, civil society, and the scientific community. The research outcome will add value to effective climate action because policymakers can make informed decisions by looking at the diverse public opinion on a comprehensive platform.

Related papers

• Identifying Climate Targets in National Laws and Policies using Machine Learning [0.0]
  We present an approach for extracting mentions of climate targets from national laws and policies. We create an expert-annotated dataset identifying three categories of target ('Net Zero', 'Reduction' and 'Other') We investigate bias and equity impacts related to our model and identify specific years and country names as problematic features.
  arXiv  Detail & Related papers  (2024-04-03T15:55:27Z)
• ClimateNLP: Analyzing Public Sentiment Towards Climate Change Using Natural Language Processing [0.0]
  This paper employs natural language processing (NLP) techniques to analyze climate change discourse and quantify the sentiment of climate change-related tweets. The objective is to discern the sentiment individuals express and uncover patterns in public opinion concerning climate change.
  arXiv  Detail & Related papers  (2023-10-12T07:48:50Z)
• AI For Global Climate Cooperation 2023 Competition Proceedings [77.07135605362795]
  No global authority can ensure compliance with international climate agreements. RICE-N supports modeling regional decision-making using AI agents. The IAM then models the climate-economic impact of those decisions into the future.
  arXiv  Detail & Related papers  (2023-07-10T20:05:42Z)
• Climate Policy Tracker: Pipeline for automated analysis of public climate policies [3.3509104620016092]
  We use a Latent Dirichlet Allocation-based pipeline for the automatic summarization and analysis of 10-years of national energy and climate plans. We focus on analyzing policy framing, the language used to describe specific issues, to detect essential nuances in the way governments frame their climate policies.
  arXiv  Detail & Related papers  (2022-11-10T20:19:28Z)
• AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N [75.67460895629348]
  Achieving long-term cooperation on climate change mitigation with n strategic agents poses a complex game-theoretic problem. We introduce RICE-N, a multi-region integrated assessment model that simulates the global climate and economy. We describe how to use multi-agent reinforcement learning to train rational agents using RICE-N.
  arXiv  Detail & Related papers  (2022-08-15T04:38:06Z)
• Climate Change & Computer Audition: A Call to Action and Overview on Audio Intelligence to Help Save the Planet [98.97255654573662]
  This work provides an overview of areas in which audio intelligence can contribute to overcome climate-related challenges. We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether.
  arXiv  Detail & Related papers  (2022-03-10T13:32:31Z)
• ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods [89.61670857155173]
  We present our solution to simulate photo-realistic floods on authentic images. We propose ClimateGAN, a model that leverages both simulated and real data for unsupervised domain adaptation and conditional image generation.
  arXiv  Detail & Related papers  (2021-10-06T15:54:57Z)
• Powering Effective Climate Communication with a Climate Knowledge Base [1.951890354110457]
  We aim to build a system that presents to any individual the climate information predicted to best motivate and inspire them to take action given their unique set of personal values. The system relies on a knowledge base (ClimateKB) of causes and effects of climate change, and their associations to personal values. We plan to open source the ClimateKB and associated code to encourage future research and applications.
  arXiv  Detail & Related papers  (2021-07-23T17:02:06Z)
• Analyzing Sustainability Reports Using Natural Language Processing [68.8204255655161]
  In recent years, companies have increasingly been aiming to both mitigate their environmental impact and adapt to the changing climate context. This is reported via increasingly exhaustive reports, which cover many types of climate risks and exposures under the umbrella of Environmental, Social, and Governance (ESG) We present this tool and the methodology that we used to develop it in the present article.
  arXiv  Detail & Related papers  (2020-11-03T21:22:42Z)
• Dynamical Landscape and Multistability of a Climate Model [64.467612647225]
  We find a third intermediate stable state in one of the two climate models we consider. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production drastically change the topography of Earth's climate.
  arXiv  Detail & Related papers  (2020-10-20T15:31:38Z)
• From Talk to Action with Accountability: Monitoring the Public Discussion of Policy Makers with Deep Neural Networks and Topic Modelling [0.0]
  We propose a multi-source topic aggregation system (MuSTAS) MuSTAS processes policy makers speech and rhetoric from several publicly available sources into an easily digestible topic summary. This topic digest will serve the general public and civil society in assessing where, how, and when politicians talk about climate and climate policies.
  arXiv  Detail & Related papers  (2020-10-16T12:21:01Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.