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Center of Competence for Sustainable Finance


Climatext is a dataset for sentence-based climate change topic detection. The dataset explores different approaches to identify the climate change topic in various text sources and is based on the paper ClimaText: A Dataset for Climate Change Topic Detection by Francesco S. Varini, Jordan Boyd-Graber, Massimiliano Ciaramita, Markus Leippold.

*Accepted for the Tackling Climate Change with Machine Learning workshop at NeurIPS 2020.

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Please cite the following paper for the use of the dataset:
Francesco S. Varini and Jordan Boyd-Graber and Massimiliano Ciaramita and Markus Leippold (2020). ClimaText: A Dataset for Climate Change Topic Detection, In: Tackling Climate Change with Machine Learning workshop at NeurIPS 2020, Online, 11 December 2020 - 11 December 2020.


The data set is composed of different tab-separated-values (tsv) files. Each tsv file contains at least four columns : "id", "label", "title", "sentence". Optionally, also a "paragraph" column.

The "label" can be either -1 (unlabeled), 0 (negative), 1 (positive), where positive means that the sentence talks about climate change and negative that it does not. 
The "title" can be either the title of a document or the link to a webpage from which the sentence was taken.

The "paragraph" can be -1 (unspecified) or a positive integer number which represents the paragraph in the text indexed in ascending order where the sentence was taken.

Document-labeled sentences
train-data\Wiki-Doc-Train.tsv, dev-data\Wiki-Doc-Dev.tsv, test-data\Wiki-Doc-Test.tsv contain document-labeled sentences

Unlabeled sentences
train-data\10-Ks (2014) unlabeled.tsv, test-data\10-Ks (2018) unlabeled.tsv

Human-labeled sentences
train-data\AL-10Ks.tsv, train-data\AL-Wiki.tsv, dev-data\Wikipedia (dev).tsv, test-data\Claims (test).tsv, test-data\Wiki-Doc-Test.tsv, test-data\Wikipedia (test).tsv

Human-labeled sentences, other than the Claims, come from the bigger Document-Labeled or Unlabeled data sets (can be mapped through the "id").
For more information on the data please read the paper "ClimaText: A Dataset for Climate Change Topic Detection".