dc_revision: Extract Revision Discourse Connectors in Context
In trinker/discon: Discourse Connectors Analysis

Description Usage Arguments Value References See Also Examples

dc_revision - Extract revision discourse connectors in context.

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dc_revision(text.var, grouping.var, n.before = 1, tot = FALSE,
  n.after = n.before, ord.inds = TRUE, markup = c("<<", ">>"),
  name = "revision", ...)

`text.var`	The text variable.
`grouping.var`	The grouping variables. Also takes a single grouping variable or a list of 1 or more grouping variables.
`n.before`	The number of rows before the indexed occurrence.
`tot`	logical. If `TRUE` condenses sub-units (e.g., sentences) into turns of talk for that `grouping.var`.
`n.after`	The number of rows after the indexed occurrence.
`ord.inds`	logical. If `TRUE` inds is ordered least to greatest.
`markup`	A character vector of length two indicating the left (element 1) and right (element 2) boundary markers to use to highlight the revision discourse connectors. Use `c("", "")` to not mark the revision discourse markers.
`name`	A string indicating the name to search for within the internal data sets, typically the function's name. Generally, for internal use.
`...`	Other arguments passed to `termco`.

dc_revision - Returns returns a list of 2:

`counts`	A `termco` object of revision discourse connector counts.
`revision`	A `trans_context` object of revision discourse connectors in context.

Alemany, L. A. (2005). Representing discourse for automatic text summarization via shallow NLP techniques (Unpublished doctoral dissertation). Universitat de Barcelona, Barcelona.

http://russell.famaf.unc.edu.ar/~laura/shallowdisc4summ/discmar

termco, trans_context

out <- with(pres_debates2012[1:200, ], dc_revision(dialogue, person))
out[1]
out[2]
plot(out)

## Save externally use .doc or .txt
## print(out[[2]], file="revision_causality.doc")