eHDPrep (version 1.3.3)

extract_freetext: Extract information from free text

Description

Extracts information from specified free text variables (...) which occur in a minimum amount of rows (min_freq) and appends new variables to data.

Usage

extract_freetext(data, id_var, min_freq = 1, ...)

Value

data with additional Boolean variables describing skipgrams in

...

Arguments

data

Data frame to append skipgram variables to.

id_var

An unquoted expression which corresponds to a variable in data which identifies each row.

min_freq

Minimum percentage frequency of skipgram occurrence to return. Default = 1.

...

Unquoted expressions of free text variable names from which to extract information.

Details

New variables report the presence of skipgrams (proximal words in the text) with a minimum frequency (min_freq, default = 1%)).

References

Guthrie, D., Allison, B., Liu, W., Guthrie, L. & Wilks, Y. A Closer Look at Skip-gram Modelling. in Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06) (European Language Resources Association (ELRA), 2006).

Benoit K, Watanabe K, Wang H, Nulty P, Obeng A, Müller S, Matsuo A (2018). “quanteda: An R package for the quantitative analysis of textual data.” _Journal of Open Source Software_, *3*(30), 774. doi:10.21105/joss.00774 <https://doi.org/10.21105/joss.00774>, <https://quanteda.io>.

Feinerer I, Hornik K (2020). _tm: Text Mining Package_. R package version 0.7-8, <https://CRAN.R-project.org/package=tm>.

Ingo Feinerer, Kurt Hornik, and David Meyer (2008). Text Mining Infrastructure in R. Journal of Statistical Software 25(5): 1-54. URL: https://www.jstatsoft.org/v25/i05/.

See Also

Principle underlying function: tokens_ngrams

Other free text functions: skipgram_append(), skipgram_freq(), skipgram_identify()

Examples

data(example_data)
extract_freetext(example_data, patient_id, min_freq = 0.6, free_text)