A library for corpus analysis using the Corpus Workbench (CWB) as an efficient back end for indexing and querying large corpora.
The package offers functionality to flexibly create partitions and to carry out basic statistical operations (count, co-occurrences etc.). The original full text of documents can be reconstructed and inspected at any time. Beyond that, the package is intended to serve as an interface to packages implementing advanced statistical procedures. Respective data structures (document term matrices, term co- occurrence matrices etc.) can be created based on the indexed corpora.
A session registry directory (see
registry()) combines the registry
files for corpora that may reside in anywhere on the system. Upon loading
polmineR, the files in the registry directory defined by the
environment variable CORPUS_REGISTRY are copied to the session registry
directory. To see whether the environment variable CORPUS_REGISTRY is set,
Sys.getenv()-function. Corpora wrapped in R data packages can be
activated using the function
The package includes a draft shiny app that can be called using
polmineR.p_attribute: The default positional attribute
polmineR.left: Default value for left context.
polmineR.lineview: A logical value, whether ...
polmineR.mdsub:A list of pairs of character vectors defining regular expression substitutions applied as part of preprocessing documents for html display. Intended usage: Remove characters that would be misinterpreted as markdown formatting instructions.
polmineR.corpus_registry: The system corpus registry directory defined by the environment variable CORPUS_REGISTRY before the polmineR package has been loaded. The polmineR package uses a temporary registry directory to be able to use corpora stored at multiple locations in one session. The path to the system corpus registry directory captures this setting to keep it available if necessary.
logical value, whether polmineR is
used in the context of a shiny app. Used to control the apprearance of
progress bars depending on whether shiny app is running, or not.
polmineR.warn.size: When generating HTML table widgets (e.g.
when preparing kwic output to be displayed in RStudio's Viewe pane), the
DT::datatable() that is used internally will issue a
warning by default if the object size of the table is greater than 1500000.
The warning adresses a client-server scenario that is not applicable in the
context of a local RStudio session, so you may want to turn it of.
Internally, the warning can be suppressed by setting the option
FALSE. The polmineR option
polmineR.warn.size is processed by functions calling DT::datatable()
to set and reset the value of
DT.warn.size. Please note: The
formulation of the warning does not match the scenario of a local RStudio
session, but it may still be useful to get a warning when tables are large
and slow to process. Therefore, the default value of the setting is
Andreas Blaette (firstname.lastname@example.org)
Jockers, Matthew L. (2014): Text Analysis with R for Students of Literature. Cham et al: Springer.
Baker, Paul (2006): Using Corpora in Discourse Analysis. London: continuum.
use("polmineR") # activate demo corpora included in the package use(pkg = "RcppCWB", corpus = "REUTERS") # The package includes two sample corpora corpus("REUTERS") %>% show_info() corpus("GERMAPARLMINI") %>% show_info() # Core methods applied to corpus C <- count("REUTERS", query = "oil") C <- count("REUTERS", query = c("oil", "barrel")) C <- count("REUTERS", query = '"Saudi" "Arab.*"', breakdown = TRUE, cqp = TRUE) D <- dispersion("REUTERS", query = "oil", s_attribute = "id") K <- kwic("REUTERS", query = "oil") CO <- cooccurrences("REUTERS", query = "oil") # Core methods applied to partition kuwait <- partition("REUTERS", places = "kuwait", regex = TRUE) C <- count(kuwait, query = "oil") D <- dispersion(kuwait, query = "oil", s_attribute = "id") K <- kwic(kuwait, query = "oil", meta = "id") CO <- cooccurrences(kuwait, query = "oil") # Go back to full text p <- partition("REUTERS", id = 127) if (interactive()) read(p) h <- html(p) h_highlighted <- highlight(h, highlight = list(yellow = "oil")) if (interactive()) h_highlighted # Generate term document matrix pb <- partition_bundle("REUTERS", s_attribute = "id") cnt <- count(pb, p_attribute = "word") tdm <- as.TermDocumentMatrix(cnt, col = "count")
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