Natural Language Processing (NLP) for Policy Recommendations in Carbon Management

Vertika Agarwal · Shalini Verma · Ankur Singh Bist · Untung Rahardja · Pawan Kumar Goel

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Computational and Text Analysis Methods Climate Change Policy and Economics Sentiment Analysis and Opinion Mining

Abstract

Carbon management has become an integral aspect of sustainable policy management to streamline with the accelerating challenges of climate. This chapter examines the exploration of NLP (Natural Language Processing) with policy recommendation frameworks in carbon management. NLP can automatically review and summarize hundreds of research papers on topics like carbon capture, renewable energy technologies, and emission reduction strategies. This allows policymakers to access up-to-date scientific findings without manual reading of every paper. Techniques such as topic modeling can uncover emerging themes in carbon management research, guiding investment and regulatory priorities. Monitoring social media, news articles, and public forums using NLP can provide real-time feedback on public opinion regarding proposed carbon policies. This helps policymakers understand community support or concerns.

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