imperative: Intuitively Remark Sentences as Imperative

Description Usage Arguments Value Warning Examples

Description

Automatic imperative remarking.

Usage

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  imperative(dataframe, person.var, text.var,
    lock.incomplete = FALSE, additional.names = NULL,
    parallel = FALSE, warning = FALSE)

Arguments

dataframe

A data.frame object.

person.var

The person variable.

text.var

The text variable.

lock.incomplete

logical. If TRUE locks incomplete sentences (sentences ending with "|") from being marked as imperative.

additional.names

Additional names that may be used in a command (people in the context that do not speak).

parallel

logical. If TRUE attempts to run the function on multiple cores. Note that this may not mean a speed boost if you have one core or if the data set is smaller as the cluster takes time to create. With the mraja1spl data set, with an 8 core machine, imperative had 1/3 the running time.

warning

logical. If TRUE provides comma warnings (sentences that contain numerous commas that may be handled incorrectly by the algorithm).

Value

Returns a dataframe with a text variable indicating imperative sentences. Imperative sentences are marked with * followed by the original end mark.

Warning

The algorithm used by imperative is sensitive to English language dialects and types. Commas can indicate a choppy sentence and may indicate a false positive.

Examples

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dat <- data.frame(name=c("sue", rep(c("greg", "tyler", "phil",
    "sue"), 2)), statement=c("go get it|", "I hate to read.",
    "Stop running!", "I like it!", "You are terrible!", "Don't!",
    "Greg, go to the red, brick office.", "Tyler go to the gym.",
    "Alex don't run."), stringsAsFactors = FALSE)

imperative(dat, "name", "statement", , c("Alex"))
imperative(dat, "name", "statement", lock.incomplete = TRUE, c("Alex"))
imperative(dat, "name", "statement", , c("Alex"), warning=TRUE)
imperative(dat, "name", "statement", , c("Alex"), warning=TRUE,
    parallel = TRUE)

trinker/qdap2 documentation built on May 31, 2019, 9:47 p.m.