A deterministic stratified sample of 165 abstracts (up to 40 per year,
2020–2024) from a Scopus export of COVID-19 education research, the same
source corpus used by the sbert package's topic-modeling articles.
Rebuilt by data-raw/covid_abstracts.R.
Format
A data frame with 165 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).
Examples
hg <- text_hypergraph(covid_abstracts, column = "abstract", id = "doc")
hg
#> Text hypergraph: 165 documents, 4114 words (documents as nodes, weight = n)
#> Hyperedges: 4114 (words); sizes 1-165, median 1
#> doc word count weight
#> 2-s2.0-85085897904 access 1 1
#> 2-s2.0-85085897904 affects 2 2
#> 2-s2.0-85085897904 all 2 2
#> 2-s2.0-85085897904 alternative 1 1
#> 2-s2.0-85085897904 american 1 1
#> 2-s2.0-85085897904 and 6 6
#> 2-s2.0-85085897904 any 1 1
#> 2-s2.0-85085897904 apart 1 1
#> 2-s2.0-85085897904 are 3 3
#> 2-s2.0-85085897904 article 1 1
#> ... 17876 more rows