An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction R package sentometrics version 1.0.1 CRAN Task View: NaturalLanguageProcessing (https://CRAN.R-project.org/view=NaturalLanguageProcessing) Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2021) <doi:10.18637/jss.v099.i02>. Software Depends: R (>= 3.3.0) Imports: caret, compiler, data.table, foreach, ggplot2, glmnet, ISOweek, quanteda, Rcpp (>= 0.12.13), RcppRoll, RcppParallel, stats, stringi, utils LinkingTo: Rcpp, RcppArmadillo, RcppParallel Suggests: covr, doParallel, e1071, lexicon, MCS, NLP, parallel, randomForest, stopwords, testthat, tm Samuel Borms <borms_sam@hotmail.com> Comprehensive R Archive Network (CRAN) Samuel Borms [aut, cre] (ORCID: <https://orcid.org/0000-0001-9533-1870>), David Ardia [aut] (ORCID: <https://orcid.org/0000-0003-2823-782X>), Keven Bluteau [aut] (ORCID: <https://orcid.org/0000-0003-2990-4807>), Kris Boudt [aut] (ORCID: <https://orcid.org/0000-0002-1000-5142>), Jeroen Van Pelt [ctb], Andres Algaba [ctb] GPL (>= 2) 2025-04-03 application/tgz https://CRAN.R-project.org/package=sentometrics doi:10.32614/CRAN.package.sentometrics