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Score emoji in a text column against any lexicon

Source: R/emoji-lexicon-api.R
emoji_score.Rd

emoji_score() is the generic scorer that the friendly verbs (emoji_sentiment(), emoji_emotion()) sit on top of. It joins each row's emoji to lexicon through emoji_key() and returns the per-row mean of the score column, plus the number of emoji scored. Bring your own lexicon, or name a bundled / registered one.

Usage

emoji_score(data, text, lexicon, by = "emoji", score = NULL)

Arguments

data

A data frame or tibble containing a text column.

text

The text column to scan, supplied unquoted.

lexicon

Either a string naming a bundled or registered lexicon, or a data frame. For data frames, by names the glyph column and score the score column.

by

Glyph column name when lexicon is a data frame. Default "emoji".

score

Score column name when lexicon is a data frame. If NULL, "sentiment_score" then "score" are tried.

Value

data, as a tibble, with .emoji_score (per-row mean), .emoji_n_scored (emoji found in the lexicon) and .emoji_n (total emoji) added. For the multi-dimensional "emotag1200" lexicon the score is the mean over its eight emotion dimensions; use emoji_emotion() for the per-emotion profile.

See also

emoji_lexicons(), register_emoji_lexicon().

Examples

df <- data.frame(text = c("love \U0001f60d", "angry \U0001f621", "meh"))
emoji_score(df, text, lexicon = "novak2015")
#> # A tibble: 3 × 4
#>   text     .emoji_score .emoji_n_scored .emoji_n
#>   <chr>           <dbl>           <int>    <int>
#> 1 love 😍         0.678               1        1
#> 2 angry 😡       -0.173               1        1
#> 3 meh            NA                  NA        0

# a bring-your-own lexicon
own <- data.frame(emoji = c("\U0001f600", "\U0001f621"),
                  score = c(0.9, -0.8))
emoji_score(df, text, lexicon = own)
#> # A tibble: 3 × 4
#>   text     .emoji_score .emoji_n_scored .emoji_n
#>   <chr>           <dbl>           <int>    <int>
#> 1 love 😍          NA                 0        1
#> 2 angry 😡         -0.8               1        1
#> 3 meh              NA                NA        0