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>.
Version: 1.0.1 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 Published: 2025-04-03 DOI: 10.32614/CRAN.package.sentometrics Author: Samuel Borms [aut, cre], David Ardia [aut], Keven Bluteau [aut], Kris Boudt [aut], Jeroen Van Pelt [ctb], Andres Algaba [ctb] Maintainer: Samuel Borms <borms_sam at hotmail.com> BugReports: https://github.com/SentometricsResearch/sentometrics/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://sentometrics-research.com/sentometrics/ NeedsCompilation: yes SystemRequirements: GNU make Citation: sentometrics citation info Materials: README NEWS In views: NaturalLanguageProcessing CRAN checks: sentometrics results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=sentometrics to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4