Progress on climate action: a multilingual machine learning analysis of the global stocktake

Author:

Sietsma Anne J.ORCID,Groenendijk Rick W.ORCID,Biesbroek RobbertORCID

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science,Global and Planetary Change

Reference27 articles.

1. Asmussen CB, Møller C (2019) Smart literature review: a practical topic modelling approach to exploratory literature review. J Big Data 6:93

2. Callaghan MW, Minx JC, Forster PM (2020) A topography of climate change research. Nat Clim Chang 10:118–123

3. Chang J, Gerrish S, Wang C, Boyd-Graber J, Blei D (2009) Reading tea leaves: how humans interpret topic models. Adv Neural Inf Process Syst 22. https://proceedings.neurips.cc/paper_files/paper/2009/hash/f92586a25bb3145facd64ab20fd554ff-Abstract.html

4. Christiansen L, Olhoff A, Dale T (2020) Understanding adaptation in the Global Stocktake. iGSTDesigning a Robust Stocktake Discussion Series. UNEP DTU Partnership

5. Climate Policy Radar (2023) Global stocktake documents [dataset version afb39e3]. Huggingface. https://doi.org/10.57967/hf/1112

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