Package: sentiment.ai
Type: Package
Title: Simple Sentiment Analysis Using Deep Learning
Version: 0.1.1
Authors@R: 
  c(person('Ben', 'Wiseman',
           role    = c('cre', 'aut', 'ccp'),
           email   = 'benjamin.h.wiseman@gmail.com'),
    person('Steven', 'Nydick',
           role    = c('aut'),
           email   = 'swnydick@gmail.com',
           comment = c(ORCID = "0000-0002-2908-1188")),
    person('Tristan', 'Wisner',
           role    = c('aut'),
           email   = 'tristan.wisner@kornferry.com'),
    person('Fiona', 'Lodge',
           role    = c('ctb'),
           email   = 'fiona.lodge@kornferry.com'),
    person('Yu-Ann', 'Wang',
           role    = c('ctb'),
           email   = 'yu-ann-wang@kornferry.com'),
    person('Veronica', 'Ge',
           role    = c('art'),
           email   = 'veronica.ge@kornferry.com'),
    person('Korn Ferry Institute', 
           role = c('fnd'),
           email = 'KFInstituteRequests@KornFerry.com'))
Maintainer: Ben Wiseman <benjamin.h.wiseman@gmail.com>
Description: Sentiment Analysis via deep learning and gradient boosting models with a lot of the underlying hassle taken care of to make the process as simple as possible. 
  In addition to out-performing traditional, lexicon-based sentiment analysis (see <https://benwiseman.github.io/sentiment.ai/#Benchmarks>),
  it also allows the user to create embedding vectors for text which can be used in other analyses.
  GPU acceleration is supported on Windows and Linux.
URL: https://benwiseman.github.io/sentiment.ai/,
        https://github.com/BenWiseman/sentiment.ai
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
VignetteBuilder: knitr
Depends: R (>= 4.0.0)
Imports: data.table (>= 1.12.8), jsonlite, reticulate (>= 1.16),
        roperators (>= 1.2.0), stats, tensorflow (>= 2.2.0), tfhub (>=
        0.8.0), utils, xgboost
Suggests: rmarkdown, knitr, magrittr, microbenchmark, prettydoc,
        rappdirs, rstudioapi, text2vec (>= 0.6)
Collate: 'package-sentiment_ai.R' 'init_and_install.R' 'sentiment.R'
        'choose_model.R' 'data-default_data.R' 'data-example_data.R'
        'object-sentiment_env.R' 'matrix_helpers.R' 'constants.R'
        'create_error_text.R' 'utils-data-table.R' 'globals.R'
        'local_from_reticulate.R'
NeedsCompilation: no
Packaged: 2022-03-18 19:01:00 UTC; benaparte
Author: Ben Wiseman [cre, aut, ccp],
  Steven Nydick [aut] (<https://orcid.org/0000-0002-2908-1188>),
  Tristan Wisner [aut],
  Fiona Lodge [ctb],
  Yu-Ann Wang [ctb],
  Veronica Ge [art],
  Korn Ferry Institute [fnd]
Repository: CRAN
Date/Publication: 2022-03-19 00:00:05 UTC
Built: R 4.6.0; ; 2026-04-29 07:48:22 UTC; unix
