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.