A random sample of 1,000 COVID-19 education research abstracts

A simple random sample of 1,000 abstracts from the Scopus export of COVID-19 education research that the sbert package also uses (4,187 records, 2020–2024). Records without an abstract of at least 400 characters are excluded before sampling, and an abstract that appears twice is kept once. The years are represented in the proportions of the source. Rebuilt by data-raw/covid_sample.R.

Usage

covid_sample

Format

A data frame with 1,000 rows and 4 columns:

doc: Scopus EID, the unique document identifier.
title: Article title.
abstract: Abstract text (each at least 400 characters).
year: Publication year (integer, 2020–2024).

Source

Scopus export of COVID-19 education research, 2020–2024.

Examples

hg <- text_hypergraph(covid_sample, column = "abstract", id = "doc",
                      stop_words = stop_words_en(), min_count = 5)
#> vocabulary pruned to 3325 of 10009 words, retaining 90.79% of tokens
hg
#> Text hypergraph: 1000 documents, 3325 words (documents as nodes, weight = n)
#> Hyperedges: 3325 (words); sizes 1-870, median 10
#>                 doc       word count weight
#>  2-s2.0-85082857029   addition     1      1
#>  2-s2.0-85082857029   although     1      1
#>  2-s2.0-85082857029    attempt     1      1
#>  2-s2.0-85082857029 background     1      1
#>  2-s2.0-85082857029      basic     1      1
#>  2-s2.0-85082857029 beneficial     1      1
#>  2-s2.0-85082857029     bridge     1      1
#>  2-s2.0-85082857029       care     1      1
#>  2-s2.0-85082857029    centers     1      1
#>  2-s2.0-85082857029  challenge     1      1
#> ... 80985 more rows