Sentence Splitting


sentSplit(dataframe, text.var, rm.var = NULL, endmarks = c("?", ".", "!", "|"), incomplete.sub = TRUE, rm.bracket = TRUE, stem.col = FALSE, = "right", verbose =, ...)
sentCombine(text.var, grouping.var = NULL, as.list = FALSE)
sent_detect(text.var, endmarks = c("?", ".", "!", "|"), incomplete.sub = TRUE, rm.bracket = TRUE, ...)


A dataframe that contains the person and text variable.
The text variable.
An optional character vector of 1 or 2 naming the variables that are repeated measures (This will restart the "tot" column).
A character vector of endmarks to split turns of talk into sentences.
logical. If TRUE detects incomplete sentences and replaces with "|".
logical. If TRUE removes brackets from the text.
logical. If TRUE stems the text as a new column.
A character string giving placement location of the text column. This must be one of the strings "original", "right" or "left".
logical. If TRUE select diagnostics from check_text are reported.
The grouping variables. Default NULL generates one word list for all text. Also takes a single grouping variable or a list of 1 or more grouping variables.
logical. If TRUE returns the output as a list. If FALSE the output is returned as a dataframe.
A tot column from a sentSplit output.
Additional options passed to stem2df.

Sentence Splitting


sentSplit - returns a dataframe with turn of talk broken apart into sentences. Optionally a stemmed version of the text variable may be returned as well.

sentCombine - returns a list of vectors with the continuous sentences by grouping.var pasted together. returned as well.

TOT - returns a numeric vector of the turns of talk without sentence sub indexing (e.g. 3.2 become 3).

sent_detect - returns a character vector of sentences split on endmark.


sentSplit - Splits turns of talk into individual sentences (provided proper punctuation is used). This procedure is usually done as part of the data read in and cleaning process.

sentCombine - Combines sentences by the same grouping variable together.

TOT - Convert the tot column from sentSplit to turn of talk index (no sub sentence). Generally, for internal use.

sent_detect - Detect and split sentences on endmark boundaries.


sentSplit requires the dialogue (text) column to be cleaned in a particular way. The data should contain qdap punctuation marks (c("?", ".", "!", "|")) at the end of each sentence. Additionally, extraneous punctuation such as abbreviations should be removed (see replace_abbreviation). Trailing sentences such as I thought I... will be treated as incomplete and marked with "|" to denote an incomplete/trailing sentence.


It is recommended that the user runs check_text on the output of sentSplit's text column.


## <strong>Not run</strong>: # ## `sentSplit` EXAMPLE: # (out <- sentSplit(DATA, "state")) # out %&% check_text() ## check output text # sentSplit(DATA, "state", stem.col = TRUE) # sentSplit(DATA, "state", = "left") # sentSplit(DATA, "state", = "original") # sentSplit(raj, "dialogue")[1:20, ] # # ## plotting # plot(out) # plot(out, grouping.var = "person") # # out2 <- sentSplit(DATA2, "state", rm.var = c("class", "day")) # plot(out2) # plot(out2, grouping.var = "person") # plot(out2, grouping.var = "person", rm.var = "day") # plot(out2, grouping.var = "person", rm.var = c("day", "class")) # # ## `sentCombine` EXAMPLE: # dat <- sentSplit(DATA, "state") # sentCombine(dat$state, dat$person) # truncdf(sentCombine(dat$state, dat$sex), 50) # # ## `TOT` EXAMPLE: # dat <- sentSplit(DATA, "state") # TOT(dat$tot) # # ## `sent_detect` # sent_detect(DATA$state) # ## <strong>End(Not run)</strong>

See also

bracketX, incomplete_replace, stem2df , TOT


Dason Kurkiewicz and Tyler Rinker .