Authors@R: person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = c("aut", "cre", "cph"))
Description: A word embeddings-based semisupervised model for document scaling Watanabe (2017) <doi:10.1177/0267323117695735>.
LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
Depends: quanteda (>= 2.0), quanteda.textmodels, methods, R (>= 3.5.0)
Imports: digest, Matrix, RSpectra, irlba, rsvd, rsparse, proxyC,
stringi, grDevices, stats, ggplot2, ggrepel, reshape2, e1071

grDevices, stats, ggplot2, ggrepel, reshape2, e1071

Title: Model for Semisupervised Text Analysis Based on Word Embeddings
Description: A word embeddings-based semisupervised models for document scaling Watanabe (2017) <doi:10.1177/0267323117695735>.

Description: A word embeddings-based semisupervised models for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>.
Imports: stringi, digest, Matrix, RSpectra, irlba, rsvd, rsparse,
proxyC, grDevices, stats, ggplot2, ggrepel, reshape2, e1071,

Description: A word embeddings-based semisupervised model for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>.
It can generate word vectors on a users-provided corpus or incorporate a pre-trained word vectors.
Imports: quanteda (>= 2.0), quanteda.textmodels, quanteda.textstats,
stringi, digest, Matrix, RSpectra, irlba, rsvd, rsparse,

Imports: quanteda (>= 2.0), quanteda.textstats, stringi, digest,
Matrix, RSpectra, irlba, rsvd, rsparse, proxyC, grDevices,
stats, ggplot2, ggrepel, reshape2, e1071, locfit

Matrix, RSpectra, irlba, rsvd, rsparse, proxyC, stats, ggplot2,

Title: Semisupervised Document Scaling by Word-Embedding Models

Title: Semisupervised Document Scaling with Word-Embedding Models

Title: Functions to Replicate the Center for Disease Control and
person("Stephen", "Bertke", , "nioshltas@cdc.gov", role = c("aut", "cre"))
Description: A suite of functions for reading in a rate file in XML format,
stratify a cohort, and calculate 'SMRs' from the stratified cohort and rate file.
Imports: dplyr, knitr, lubridate, magrittr, purrr, readr, rlang,