Only the incorrect responses that were changed during spell-check Also converts all upper-case letters to lower caseĪll responses regardless of spell-checking changes The original response matrix that has had white spaces before andĪfter words response. This can be used as a final dataset for analyses (e.g., fluency of responses) A response that a participant has provided is a ' 1'Īnd a response that a participant has not provided is a ' 0'Ī response matrix that has been spell-checked and de-pluralized with duplicates removed. This function returns a list containing the following objects:Ī matrix of responses where each row represents a participantĪnd each column represents a unique response. Set to "all" to keep all punctuation charactersĪ result previously unfinished that still needs to be completed.Īllows you to continue to manually spell-check their data Set to "choose" to open an interactive directory explorerĪllows punctuation characters to be included in responses. Path to additional dictionaries to be found.ĭOES NOT search recursively (through all folders in path) (See SemNetDictionaries for more details)įor British spelling (e.g., colour, grey, programme, theatre)įor American spelling (e.g., color, gray, program, theater) Use dictionaries() or find.dictionaries() for more options A message will notify the user how IDs were assignedĬan be a vector of a corpus or any text for comparison.ĭictionary to be used for more efficient text cleaning.ĭefaults to NULL, which will use general.dictionary If no IDs are provided, then their order in the corresponding Participant IDs will be automatically identified if they are included. Textcleaner ( data = NULL, miss = 99, partBY = c ( "row", "col" ), dictionary = NULL, spelling = c ( "UK", "US" ), add.path = NULL, keepStrings = FALSE, allowPunctuations = c ( "-", "all" ), allowNumbers = FALSE, lowercase = TRUE, continue = NULL )
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