An all-in-one R package for the assessment of linguistic matching and/or accommodation.
- Input raw text, a document-term matrix (DTM), or LIWC output.
- Apply various weighting functions to a DTM.
- Measure similarity and/or accommodation with various metrics.
- Calculate standard forms of Language Style Matching (LSM) and Latent Semantic Similarity (LSS).
Download R from r-project.org, then install the package from an R console:
Release (version 1.0.5)
Development (version 1.0.6)
# install.packages('remotes') remotes::install_github('miserman/lingmatch')
And load the package:
Can make a quick comparison between two bits of text; by default this will give the cosine similarity between raw word-count vectors:
lingmatch('First text to look at.', 'Text to compare that text with.')
Or, given a vector of texts:
text = c( "Why, hello there! How are you this evening?", "I am well, thank you for your inquiry!", "You are a most good at social interactions person!", "Why, thank you! You're not all bad yourself!" )
Process the texts in one step:
# with a dictionary inquirer_cats = lma_process(text, dict = 'inquirer', dir = '~/Dictionaries') # with a latent semantic space glove_vectors = lma_process(text, space = 'glove', dir = '~/Latent Semantic Spaces')
Or process the texts step by step, then measure similarity between each:
dtm = lma_dtm(text) dtm_weighted = lma_weight(dtm) dtm_categorized = lma_termcat(dtm_weighted, lma_dict(1:9)) similarity = lma_simets(dtm_categorized, metric = 'canberra')
Or do that within a single function call:
Or, if you want a standard form (as in this example), specify a default:
similarity = lingmatch(text, type = 'lsm')$sim