Co-occurring emoji pairs

emoji_pairs() returns a tidy edge list of the emoji that appear together in the same document: one row per pair with the number of documents in which the pair co-occurs. By default every row of data is a document; give doc_id to treat all rows sharing an id (a conversation, a user, a day) as one document. The output mirrors widyr::pairwise_count() (item1, item2, n) and pipes straight into igraph::graph_from_data_frame(), tidygraph or ggraph.

Usage

emoji_pairs(data, text, doc_id = NULL, directed = FALSE, sort = TRUE)

Arguments

data

A data frame or tibble containing a text column. Grouped data frames are accepted. The verbs that work a row at a time (adding columns, or keeping and expanding rows) carry the grouping through to their result, as dplyr::mutate() and dplyr::filter() do. The verbs that pool across rows – the counts, the co-occurrence edge lists, the time series – warn that they ignore the grouping and return one corpus-wide answer.

text

The text column to scan, supplied unquoted. Any atomic column is accepted and read as character, so a factor works and a numeric, Date or logical one simply contains no emoji. A list column – or a data-frame column – is refused rather than coerced, because coercing one deparses it and the emoji found would be in the code rather than in your data. What counts as an emoji is the same in every verb; see the Detection section of tidyEmoji for the one case that surprises people, code points that are emoji only when they carry U+FE0F.

doc_id

Optional unquoted column identifying documents. Rows sharing a value are treated as one document. Default: each row is a document.

The result has a row per pair, so it grows with the square of the distinct emoji in a document: a day or a conversation is cheap, and pooling a whole corpus under one id is not. 800 distinct emoji in one document is 319,600 pairs and a few seconds; 3790 would be 7.2 million.

directed

If TRUE, pairs are ordered by first appearance: a document where the tears-of-joy emoji appears before the heart-eyes emoji counts towards (tears-of-joy, heart-eyes), not the reverse. Default FALSE (unordered pairs, with item1 sorted before item2).

sort

If TRUE (default), sort by descending n (ties broken by item1, item2 so the order is deterministic). FALSE sorts by item1 then item2 instead – still a fixed order, computed in the C locale, not the order the pairs happened to be counted in.

Value

A tibble with columns item1, item2 and n. Empty (but typed) when no document contains two distinct emoji.

Details

Glyphs are canonicalised through the package's codepoint key, so qualified and unqualified forms of the same emoji (with/without U+FE0F) count as one node. Pairs are between distinct emoji: repeats of the same emoji in a document do not pair with themselves (see emoji_cooccurrence() for the diagonal).

See also

emoji_cooccurrence() for the same counts with an optional diagonal; emoji_ngrams() for consecutive sequences.

Examples

df <- data.frame(text = c("fun \U0001f602\U0001f60d",
                          "\U0001f602\U0001f60d\U0001f389",
                          "just \U0001f602"))
emoji_pairs(df, text)
#> # A tibble: 3 × 3
#>   item1 item2     n
#>   <chr> <chr> <int>
#> 1 😂    😍        2
#> 2 🎉    😂        1
#> 3 🎉    😍        1
emoji_pairs(df, text, directed = TRUE)
#> # A tibble: 3 × 3
#>   item1 item2     n
#>   <chr> <chr> <int>
#> 1 😂    😍        2
#> 2 😂    🎉        1
#> 3 😍    🎉        1