sborms/sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Version 0.4

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. (2017) .

Getting started

Package details

AuthorDavid Ardia [aut], Keven Bluteau [aut], Samuel Borms [aut, cre], Kris Boudt [aut]
MaintainerSamuel Borms <[email protected]>
LicenseGPL (>= 2)
Version0.4
URL https://github.com/sborms/sentometrics
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("sborms/sentometrics")
sborms/sentometrics documentation built on June 17, 2018, 8:53 p.m.