lingmatch

An all-in-one R package for the assessment of linguistic matching and/or accommodation.

features

• 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).

resources

• Documentation and guides: miserman.github.io/lingmatch
  • Quick start
  • Comparisons
  • Introduction to text analysis
  • Word vectors
  • Text Classification
• Dictionary repository: osf.io/y6g5b
• Latent semantic space repository: osf.io/489he

installation

Download R from r-project.org, then install the package from an R console:

Release (version 1.0.2)

install.packages('lingmatch')

Development (version 1.0.3)

# install.packages('remotes')
remotes::install_github('miserman/lingmatch')

And load the package:

library(lingmatch)

examples

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:

similarity = lingmatch(
  text, weight = 'frequency', dict = lma_dict(1:9), metric = 'canberra'
)$sim

Or, if you want a standard form (as in this example), specify a default:

similarity = lingmatch(text, type = 'lsm')$sim