Published June 6, 2022 | Version v1

Impact of the COVID-19 pandemic on academic productivity

Authors/Creators

Description

This data set was used to analyse changes in academic productivity due to the COVID-19 pandemic.

Here we describe how those data were collected. We downloaded the arXiv dataset hosted by Kaggle on 2022 June 6. This dataset is a JSON file (named `arxiv-metadata-oai-snapshot.json`) compressed into a zip file. We extracted this file and then executed `process.py` to create the following three files:

- `metadata.json`: titles, abstract, and affiliations of authors

- `authors.json`: author names

- `records.csv`: arXiv identifier, categories, number of authors and affiliations, abstract length

 

We excluded pre-prints from 2022 June when processing files. The `process.py` script also adds a 'dummy' line to the `records.csv` to make Python load arXiv identifiers as strings. These three files (`metadata.json`, `authors.json`, and `records.csv`) were used for this analysis.

Files

arxiv-metadata-oai-snapshot.json

Files (5.9 GB)

Name Size
md5:40281c3de1f134f292a238bfd9a2c270
3.4 GB Preview Download
md5:0d4911842eea7167f83d44081ad02d22
379.2 MB Preview Download
md5:9f03c154d44460ab31c3b6549421b989
2.0 GB Preview Download
md5:045546b5d292b75f4b3131fff23191cc
2.9 kB Download
md5:7def1e9eab2f047dd4d4e236084c71fe
1.0 kB Preview Download
md5:75d25b305519d3c040e0d82fdd64cc90
87.6 MB Preview Download