chron, dplyr (>= 0.3), gdata, gender (>= 0.4.3), ggplot2 (>=
0.9.3.1), grid, gridExtra, igraph, methods, NLP, openNLP (>=
0.2-1), parallel, plotrix, RCurl, reports, reshape2, scales,
stringdist, tidyr, tm (>= 0.6.2), tools, venneuler, wordcloud,
xlsx, XML
Automates many of the tasks associated with quantitative
discourse analysis of transcripts containing discourse
including frequency counts of sentence types, words, sentences,
turns of talk, syllables and other assorted analysis tasks. The
package provides parsing tools for preparing transcript data.
Many functions enable the user to aggregate data by any number
of grouping variables, providing analysis and seamless
integration with other R packages that undertake higher level
analysis and visualization of text.  This affords the user a
more efficient and targeted analysis.  'qdap' is designed for
transcript analysis, however, many functions are applicable to
other areas of Text Mining/Natural Language Processing.

R (>= 3.1.0), qdapDictionaries (>= 1.0.2), qdapRegex (>=
0.1.2), qdapTools (>= 1.3.1), RColorBrewer
chron, dplyr (>= 0.3), gdata, gender (>= 0.5.1), ggplot2 (>=
0.9.3.1), grid, gridExtra, igraph, methods, NLP, openNLP (>=
0.2-1), parallel, plotrix, RCurl, reports, reshape2, scales,
stringdist, tidyr, tm (>= 0.6.2), tools, venneuler, wordcloud,
xlsx, XML

c(person("Bryan", "Goodrich", role = "ctb"), person("Dason", "Kurkiewicz", role = "ctb"),
person("Tyler", "Rinker", email = "tyler.rinker@gmail.com", role = c("aut", "cre")))
chron, dplyr (>= 0.3), gdata, gender (>= 0.5.1), ggplot2 (>=
2.1.0), grid, gridExtra, igraph, methods, NLP, openNLP (>=
0.2-1), parallel, plotrix, RCurl, reports, reshape2, scales,
stringdist, tidyr, tm (>= 0.6.2), tools, venneuler, wordcloud,
xlsx, XML
Automates many of the tasks associated with quantitative discourse analysis of transcripts
containing discourse including frequency counts of sentence types, words, sentences, turns of
talk, syllables and other assorted analysis tasks. The package provides parsing tools for
preparing transcript data. Many functions enable the user to aggregate data by any number of
grouping variables, providing analysis and seamless integration with other R packages that
undertake higher level analysis and visualization of text.  This affords the user a more
efficient and targeted analysis.  'qdap' is designed for transcript analysis, however, many
functions are applicable to other areas of Text Mining/Natural Language Processing.