The sentometrics package is an
integrated framework for textual sentiment time series
aggregation and prediction. It accounts for the intrinsic
challenge that textual sentiment can be computed in many different ways,
as well as the large number of possibilities to pool sentiment into a
time series index. The package integrates the fast
quantification of sentiment from texts, the
aggregation into different sentiment time series, and the
prediction based on these measures. All in one coherent
workflow!
See the package website and the vignette for plenty of examples and details. We also refer to our survey organized as an overview of the required steps in a typical econometric analysis of sentiment from alternative (such as textual) data, and following companion web page.
To install the package from CRAN, simply do:
install.packages("sentometrics")To install the latest development version of
sentometrics (which may contain bugs!),
execute:
devtools::install_github("SentometricsResearch/sentometrics")For a visual interface as a Shiny application of the package’s core
functionalities, install the sentometrics.app
package, and run the sento_app() function.
Please cite sentometrics in
publications. Use citation("sentometrics").
This software package originates from a Google Summer of Code 2017 project, was further developed during a follow-up Google Summer of Code 2019 project, and benefited generally from financial support by Innoviris, IVADO, swissuniversities, and the Swiss National Science Foundation (grants #179281 and #191730).