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.
Version: 0.7.4 Depends: R (≥ 3.5.0) Imports: Rcpp (≥ 1.0.4.6), methods, generics, quanteda (≥ 3.2.0), data.table (≥ 1.13.6), RcppHungarian LinkingTo: Rcpp, RcppArmadillo, RcppProgress Suggests: ggplot2, ggridges, plotly, RColorBrewer, xts, zoo, future, future.apply, progressr, progress, testthat, covr, stm, lda, topicmodels, seededlda (≥ 1.4.0), keyATM, LDAvis, servr, textcat, stringr, sentometrics, spacyr, knitr, rmarkdown, webshot Published: 2024-09-20 DOI: 10.32614/CRAN.package.sentopics Author: Olivier Delmarcelle [aut, cre], Samuel Borms [ctb], 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()) Maintainer: Olivier Delmarcelle <delmarcelle.olivier at gmail.com> BugReports: https://github.com/odelmarcelle/sentopics/issues License: GPL (≥ 3) URL: https://github.com/odelmarcelle/sentopics NeedsCompilation: yes Materials: README, NEWS CRAN checks: sentopics results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=sentopics to link to this page.
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