Word Embedding Research Framework for Psychological Science

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Documentation for package ‘PsychWordVec’ version 2023.9

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as_embed Word vectors data class: 'wordvec' and 'embed'.
as_wordvec Word vectors data class: 'wordvec' and 'embed'.
cosine_similarity Cosine similarity/distance between two vectors.
cos_dist Cosine similarity/distance between two vectors.
cos_sim Cosine similarity/distance between two vectors.
data_transform Transform plain text of word vectors into 'wordvec' (data.table) or 'embed' (matrix), saved in a compressed ".RData" file.
data_wordvec_load Load word vectors data ('wordvec' or 'embed') from ".RData" file.
data_wordvec_subset Extract a subset of word vectors data (with S3 methods).
demodata Demo data (pre-trained using word2vec on Google News; 8000 vocab, 300 dims).
dict_expand Expand a dictionary from the most similar words.
dict_reliability Reliability analysis and PCA of a dictionary.
get_wordvec Extract word vector(s).
load_embed Load word vectors data ('wordvec' or 'embed') from ".RData" file.
load_wordvec Load word vectors data ('wordvec' or 'embed') from ".RData" file.
most_similar Find the Top-N most similar words.
normalize Normalize all word vectors to the unit length 1.
orth_procrustes Orthogonal Procrustes rotation for matrix alignment.
pair_similarity Compute a matrix of cosine similarity/distance of word pairs.
pattern Word vectors data class: 'wordvec' and 'embed'.
plot_network Visualize a (partial correlation) network graph of words.
plot_similarity Visualize cosine similarity of word pairs.
plot_wordvec Visualize word vectors.
plot_wordvec_tSNE Visualize word vectors with dimensionality reduced using t-SNE.
subset.embed Extract a subset of word vectors data (with S3 methods).
subset.wordvec Extract a subset of word vectors data (with S3 methods).
sum_wordvec Calculate the sum vector of multiple words.
tab_similarity Tabulate cosine similarity/distance of word pairs.
test_RND Relative Norm Distance (RND) analysis.
test_WEAT Word Embedding Association Test (WEAT) and Single-Category WEAT.
text_init Install required Python modules in a new conda environment and initialize the environment, necessary for all 'text_*' functions designed for contextualized word embeddings.
text_model_download Download pre-trained language models from HuggingFace.
text_model_remove Remove downloaded models from the local .cache folder.
text_to_vec Extract contextualized word embeddings from transformers (pre-trained language models).
text_unmask <Deprecated> Fill in the blank mask(s) in a query (sentence).
tokenize Tokenize raw text for training word embeddings.
train_wordvec Train static word embeddings using the Word2Vec, GloVe, or FastText algorithm.
[.embed Word vectors data class: 'wordvec' and 'embed'.