Which emoji in this corpus are most likely to be misread?

emoji_flag_ambiguous() crosses the emoji actually present in a text column with their annotation-disagreement statistics and returns the most ambiguous ones first. It is the content-QA shortlist: the glyphs worth a second look before a campaign ships or a coding scheme is fixed.

Usage

emoji_flag_ambiguous(data, text, top_n = 10, measure = "entropy")

Arguments

data

A data frame or tibble containing a text column.

text

The text column to scan, supplied unquoted.

top_n

Number of emoji to return, most ambiguous first. NULL returns all of them.

measure

Ambiguity statistic to rank by; see emoji_ambiguity().

Value

A tibble with columns emoji, name, n (occurrences in the corpus), n_annotations, ambiguity and rank (the glyph's rank in the whole lexicon). Emoji absent from the lexicon cannot be ranked and are dropped.

See also

emoji_ambiguity(), emoji_risk().

Examples

df <- data.frame(text = c("ok \U0001f643", "yay \U0001f600 \U0001f643",
                          "hmm \U0001f612"))
emoji_flag_ambiguous(df, text, top_n = 3)
#> # A tibble: 2 × 6
#>   emoji name              n n_annotations ambiguity  rank
#>   <chr> <chr>         <int>         <int>     <dbl> <int>
#> 1 😒    unamused face     1          1385     0.959   233
#> 2 😀    grinning face     1           439     0.835   410