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Emoji frequency over time

Source: R/emoji-time.R
emoji_trend.Rd

emoji_trend() counts emoji per time period and returns the long table that plots directly: one row per (period, emoji) over the periods it returns, including the ones in which a given emoji is absent, so a trend line does not silently skip its zeros.

Usage

emoji_trend(
  data,
  text,
  time,
  by = "month",
  top_n = 20,
  measure = c("n", "share")
)

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.

time

Unquoted column of dates or date-times (Date, POSIXct, or character in "YYYY-MM-DD" form). A date-time is bucketed by the calendar day it displays as in its own timezone, not by its UTC day: an emoji posted at 23:30 New York time belongs to that day, not to the next one.

"Its own timezone" means the column's tzone attribute. A POSIXct created without one – which is what as.POSIXct("2024-01-01 23:30") and most CSV readers give you – has no timezone of its own, so R displays it in the session's, and the buckets follow. The same column then gives hour 23 on one machine and hour 4 on another. Tag the column (as.POSIXct(x, tz = "UTC"), or lubridate::force_tz()) if the result has to be reproducible; a Date column is immune either way.

A character column must lead with a four-digit year: "2024-01-01" or "2024/01/01", with one- or two-digit month and day, and any trailing time ignored. Values that do not parse warn and are dropped – but a column in which nothing reads as a date is an error rather than a column of NA, since there would be no time axis left. Note that "01/02/2024" is in the second group: convert a column written that way with as.Date() and its own format first.

by

Period length: "day", "week" (starting Monday), "month" (default), "quarter" or "year".

top_n

Number of emoji to follow, ranked by measure over the whole corpus. NULL keeps every emoji. Default 20. When a tie straddles the cut the glyph decides which emoji fall inside it, in the C locale, as in top_n_emojis(); a corpus with fewer emoji than this returns every one of them rather than padding, and 0 returns no rows at all.

measure

Statistic used to rank emoji for top_n and to order the rows within a period: "n" (default) or "share".

Value

A tibble with columns .period (a Date, the start of the period), emoji, name, n and share, sorted by .period, then by measure descending, then by the glyph, so the order is fully determined. That last key matters: within a period the zeros this verb fills in all tie on both of the others.

Details

Which periods appear. The grid is complete over the observed periods, and "observed" means a period holding at least one emoji. A period whose rows carry no emoji at all does not appear, and neither does a gap in the calendar: emoji_trend() never invents a period. So the zeros it fills in are the ones within the periods it returns, not a continuous time axis. Pass the result through tidyr::complete() against a calendar sequence if you need the empty periods too.

The three time verbs answer this differently, on purpose, and it is worth knowing which you are getting before joining two of them on .period:

  • emoji_trend() – periods containing at least one emoji.

  • emoji_turnover() – every period containing at least one dated row, including emoji-free ones, which report n_types = 0.

  • emoji_seasonality() – every level of the cycle unconditionally, whether or not the data reaches it. share is the emoji's count divided by all emoji tokens in the same period, which is what makes periods with different volumes comparable. top_n selects the emoji to follow, ranked over the whole corpus by measure, and the selected set is the same in every period.

Rows whose time is missing or unparseable contribute nothing. Glyphs are canonicalised through the package's codepoint key, so qualified and unqualified forms share one series.

See also

emoji_turnover() for vocabulary churn, emoji_seasonality() for cyclical patterns.

Examples

df <- data.frame(
  when = as.Date(c("2024-01-05", "2024-01-20", "2024-02-03")),
  text = c("\U0001f600 hi", "\U0001f600\U0001f602", "\U0001f602 yes")
)
emoji_trend(df, text, when)
#> # A tibble: 4 × 5
#>   .period    emoji name                       n share
#>   <date>     <chr> <chr>                  <int> <dbl>
#> 1 2024-01-01 😀    grinning face              2 0.667
#> 2 2024-01-01 😂    face with tears of joy     1 0.333
#> 3 2024-02-01 😂    face with tears of joy     1 1    
#> 4 2024-02-01 😀    grinning face              0 0