# Word Embedding Research Framework for Psychological Science

## Documentation for package ‘PsychWordVec’ version 2023.9

- DESCRIPTION file.

## Help Pages

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'.