'a la Carte' on Text (ConText) Embedding Regression

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Documentation for package ‘conText’ version 1.4.3

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

bootstrap_contrast	Bootstrap similarity and ratio computations
bootstrap_nns	Bootstrap nearest neighbors
bootstrap_ols	Bootstrap OLS
bootstrap_similarity	Boostrap similarity vector
build_conText	build a 'conText-class' object
build_dem	build a 'dem-class' object
build_fem	build a 'fem-class' object
compute_contrast	Compute similarity and similarity ratios
compute_similarity	Compute similarity vector (sub-function of bootstrap_similarity)
compute_transform	Compute transformation matrix A
conText	Embedding regression
contrast_nns	Contrast nearest neighbors
cos_sim	Compute the cosine similarity between one or more ALC embeddings and a set of features.
cr_glove_subset	GloVe subset
cr_sample_corpus	Congressional Record sample corpus
cr_transform	Transformation matrix
dem	Build a document-embedding matrix
dem_group	Average document-embeddings in a dem by a grouping variable
dem_sample	Randomly sample documents from a dem
embed_target	Embed target using either: (a) a la carte OR (b) simple (untransformed) averaging of context embeddings
feature_sim	Given two feature-embedding-matrices, compute "parallel" cosine similarities between overlapping features.
fem	Create an feature-embedding matrix
find_cos_sim	Find cosine similarities between target and candidate words
find_nns	Return nearest neighbors based on cosine similarity
get_context	Get context words (words within a symmetric window around the target word/phrase) sorrounding a user defined target.
get_cos_sim	Given a tokenized corpus, compute the cosine similarities of the resulting ALC embeddings and a defined set of features.
get_local_vocab	Identify words common to a collection of texts and a set of pretrained embeddings.
get_ncs	Given a set of tokenized contexts, find the top N nearest contexts.
get_nns	Given a tokenized corpus and a set of candidate neighbors, find the top N nearest neighbors.
get_nns_ratio	Given a corpus and a binary grouping variable, computes the ratio of cosine similarities over the union of their respective N nearest neighbors.
get_seq_cos_sim	Calculate cosine similarities between target word and candidates words over sequenced variable using ALC embedding approach
ncs	Given a set of embeddings and a set of tokenized contexts, find the top N nearest contexts.
nns	Given a set of embeddings and a set of candidate neighbors, find the top N nearest neighbors.
nns_ratio	Computes the ratio of cosine similarities for two embeddings over the union of their respective top N nearest neighbors.
permute_contrast	Permute similarity and ratio computations
permute_ols	Permute OLS
plot_nns_ratio	Plot output of 'get_nns_ratio()'
prototypical_context	Find most "prototypical" contexts.
run_ols	Run OLS
tokens_context	Get the tokens of contexts sorrounding user defined patterns