output
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NETs-Fast

Repository for the paper:

Fast growing research on negative emissions

Jan C Minx William F Lamb Max W Callaghan Lutz Bornmann Sabine Fuss Environmental Research Letters vol. 12 issue 3 (2017) pp: 035007 https://dx.doi.org/10.1088/1748-9326/aa5ee5

To reproduce the results in the paper, follow these steps.

Download data

• Enter the query in input/queries/NETS_query_v7.txt into the advanced search of Web of Science, and save the results to "Other file formats" in a folder named input/queries/NETS_query_v7

Run analysis

The scripts in scripts/R read the data and run the analysis and should be run in the following order

• project_setup.R installs all necessary packages (in the versions current at the time of writing this paper) - This may take some time...
• topic_model.R reads the abstracts, runs a topic model and saves the results in output/LDA_19_098
• The file output/LDA_19_098/index.html is a mini-site which allows you to explore the topics. The online version in this repository is here This is used to inform the topic naming - to do this, add an extra column in output/LDA_19_098/LDA_19_098_topic_terms.csv and name the topics in this column
• post_topic_model reads the new topic names, and calculates correlation networks in output/LDA_19_098/LDA_19_098_topic_correlations.graphml and output/LDA_19_098/LDA_19_098_document_correlations.graphml. The topic correlations file was imported into gephi for aesthetic work to produce the final figure in the paper
• figures.R produces Figure 2 in the paper
• growth.R produces a table of growth by discipline in discipline_growth.csv
• search.R searches the corpus for mentions of Integrated Assessment Models (IAMs)