sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Time series analysis based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in many ways. As described in Ardia et al. (2017) <>, the package provides a means to model the impact of sentiment in texts on a target variable, by first computing a wide range of textual sentiment measures and then selecting those that are most informative.

Version: 0.2
Depends: R (≥ 3.4.2), data.table, ggplot2, foreach
Imports: utils, stats, quanteda, sentimentr, stringi, zoo, abind, glmnet, caret, compiler, Rcpp (≥ 0.12.13), RcppRoll, ggthemes, ISOweek, MCS
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, e1071, randomForest
Published: 2017-11-13
Author: David Ardia [aut], Keven Bluteau [aut], Samuel Borms [aut, cre], Kris Boudt [aut]
Maintainer: Samuel Borms <samuel.borms at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: sentometrics citation info
Materials: README NEWS
CRAN checks: sentometrics results


Reference manual: sentometrics.pdf
Package source: sentometrics_0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
OS X El Capitan binaries: r-release: sentometrics_0.2.tgz
OS X Mavericks binaries: r-oldrel: not available


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