Harmonizing existing climate change mitigation policy datasets with a hybrid machine learning approach.

ABSTRACT: With the rapid proliferation of climate policies in both number and scope, there is an increasing demand for a global-level dataset that provides multi-indicator information on policy elements and their implementation contexts. To address this need, we developed the Global Climate Change Mitigation Policy Dataset (GCCMPD) using a semisupervised hybrid machine learning approach, drawing upon policy information from global, regional, and sector-specific sources. Differing from existing climate policy datasets, the GCCMPD covers a large range of policies, amounting to 73,625 policies of 216 entities. Through the integration of expert knowledge-based dictionary mapping, probability statistics methods, and advanced natural language processing technology, the GCCMPD offers detailed classificatio

SUBMITTER: Wu L 

PROVIDER: S-EPMC11150542 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature