sentometrics

An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

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. (2019) <doi:10.2139/ssrn.3067734>.

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Description file content

Package
sentometrics
Type
Package
Title
An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Version
0.8.0
Maintainer
Samuel Borms
Description
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. (2019) .
Depends
R (>= 3.3.0)
License
GPL (>= 2)
BugReports
https://github.com/sborms/sentometrics/issues
URL
Encoding
UTF-8
LazyData
true
Suggests
covr, doParallel, e1071, NLP, parallel, randomForest, testthat, tm
Imports
caret, compiler, data.table, foreach, ggplot2, glmnet, ISOweek, quanteda, Rcpp (>= 0.12.13), RcppRoll, RcppParallel, stats, stringi, utils
LinkingTo
Rcpp, RcppArmadillo, RcppParallel
RoxygenNote
7.0.2
SystemRequirements
GNU make
NeedsCompilation
yes
Packaged
2020-01-13 20:12:11 UTC; saborms
Author
Samuel Borms [aut, cre] (), David Ardia [aut] (), Keven Bluteau [aut] (), Kris Boudt [aut] (), Jeroen Van Pelt [ctb], Andres Algaba [ctb]
Repository
CRAN
Date/Publication
2020-01-13 21:10:03 UTC

install.packages('sentometrics')

0.8.0

11 days ago

https://github.com/sborms/sentometrics

Samuel Borms

GPL (>= 2)

Depends on

R (>= 3.3.0)

Imports

caret, compiler, data.table, foreach, ggplot2, glmnet, ISOweek, quanteda, Rcpp (>= 0.12.13), RcppRoll, RcppParallel, stats, stringi, utils

Suggests

covr, doParallel, e1071, NLP, parallel, randomForest, testthat, tm

Discussions