PsychWordVec

Word Embedding Research Framework for Psychological Science.

An integrative toolbox of word embedding research that provides:

1. A collection of pre-trained static word vectors in the .RData compressed format;
2. A series of functions to process, analyze, and visualize word vectors;
3. A range of tests to examine conceptual associations, including the Word Embedding Association Test (Caliskan et al., 2017) and the Relative Norm Distance (Garg et al., 2018), with permutation test of significance;
4. A set of training methods to locally train (static) word vectors from text corpora, including Word2Vec (Mikolov et al., 2013), GloVe (Pennington et al., 2014), and FastText (Bojanowski et al., 2017);
5. A group of functions to download pre-trained language models (e.g., GPT, BERT) and extract contextualized (dynamic) word vectors (based on the R package text).

⚠️ All users should update the package to version ≥ 0.3.2. Old versions may have slow processing speed and other problems.

Author

Han-Wu-Shuang (Bruce) Bao 包寒吴霜