Package: sentopics
Type: Package
Title: Tools for Joint Sentiment and Topic Analysis of Textual Data
Version: 0.7.1
Date: 2022-05-17
Authors@R: c(
  person("Olivier", "Delmarcelle", email = "delmarcelle.olivier@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4347-070X")),
  person("Samuel", "Borms", email = "samuel.borms@unine.ch", role = c("ctb"), comment = c(ORCID = "0000-0001-9533-1870")),
  person("Chengua", "Lin", email = "chenghua.lin@abdn.ac.uk", role = "cph", comment = "Original JST implementation"),
  person("Yulan", "He", email = "yulan.he@warwick.ac.uk", role = "cph", comment = "Original JST implementation"),
  person("Jose", "Bernardo", role = "cph", comment = "Original JST implementation"),
  person("David", "Robinson", , "admiral.david@gmail.com", role = "cph", comment = "Implementation of reorder_within()"),
  person("Julia", "Silge", , "julia.silge@gmail.com", role = "cph",
           comment = c("Implementation of reorder_within()", ORCID = "0000-0002-3671-836X"))
  )
Maintainer: Olivier Delmarcelle <delmarcelle.olivier@gmail.com>
Description: A framework that joins topic modeling and sentiment analysis of
  textual data. The package implements a fast Gibbs sampling estimation of
  Latent Dirichlet Allocation (Griffiths and Steyvers (2004)
  <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He,
  Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of
  helpers and visualizations to analyze the result of topic modeling. The
  framework also allows enriching topic models with dates and externally
  computed sentiment measures. A flexible aggregation scheme enables the
  creation of time series of sentiment or topical proportions from the enriched
  topic models. Moreover, a novel method jointly aggregates topic proportions
  and sentiment measures to derive time series of topical sentiment.
License: GPL (>= 3)
BugReports: https://github.com/odelmarcelle/sentopics/issues
URL: https://github.com/odelmarcelle/sentopics
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.4.6), methods, quanteda (>= 3.2.0), data.table
        (>= 1.13.6), RcppHungarian
Suggests: ggplot2, ggridges, plotly, RColorBrewer, xts, zoo, future,
        future.apply, progressr, progress, testthat, covr, stm, lda,
        topicmodels, seededlda, LDAvis, servr, textcat, stringr,
        sentometrics, spacyr, knitr, rmarkdown, webshot
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
RcppModules: model_module
RoxygenNote: 7.1.2
LazyData: true
SystemRequirements: C++11
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-05-17 14:42:17 UTC; odlmarce
Author: Olivier Delmarcelle [aut, cre]
    (<https://orcid.org/0000-0003-4347-070X>),
  Samuel Borms [ctb] (<https://orcid.org/0000-0001-9533-1870>),
  Chengua Lin [cph] (Original JST implementation),
  Yulan He [cph] (Original JST implementation),
  Jose Bernardo [cph] (Original JST implementation),
  David Robinson [cph] (Implementation of reorder_within()),
  Julia Silge [cph] (Implementation of reorder_within(),
    <https://orcid.org/0000-0002-3671-836X>)
Repository: CRAN
Date/Publication: 2022-05-18 13:20:02 UTC
Built: R 4.1.2; x86_64-apple-darwin17.0; 2022-05-19 10:46:28 UTC; unix
Archs: sentopics.so.dSYM
