Model for Semisupervised Text Analysis Based on Word Embeddings
A word embeddings-based semisupervised model for document scaling Watanabe (2020) .
LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.