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

# An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

## Documentation for package ‘sentometrics’ version 1.0.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

sentometrics-package | sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
add_features | Add feature columns to a (sento_)corpus object
aggregate.sentiment | Aggregate textual sentiment across sentences, documents and time
aggregate.sento_measures | Aggregate sentiment measures
as.data.table.sento_measures | Get the sentiment measures
as.sentiment | Convert a sentiment table to a sentiment object
as.sento_corpus | Convert a quanteda or tm corpus object into a sento_corpus object
attributions | Retrieve top-down model sentiment attributions
compute_sentiment | Compute textual sentiment across features and lexicons
corpus_summarize | Summarize the sento_corpus object
ctr_agg | Set up control for aggregation into sentiment measures
ctr_model | Set up control for sentiment-based sparse regression modeling
diff.sento_measures | Differencing of sentiment measures
epu | Monthly U.S. Economic Policy Uncertainty index
get_dates | Get the dates of the sentiment measures/time series
get_dimensions | Get the dimensions of the sentiment measures
get_hows | Options supported to perform aggregation into sentiment measures
get_loss_data | Retrieve loss data from a selection of models
list_lexicons | Built-in lexicons
list_valence_shifters | Built-in valence word lists
measures_fill | Add and fill missing dates to sentiment measures
measures_update | Update sentiment measures
merge.sentiment | Merge sentiment objects horizontally and/or vertically
nmeasures | Get number of sentiment measures
nobs.sento_measures | Get number of observations in the sentiment measures
peakdates | Extract dates related to sentiment time series peaks
peakdocs | Extract documents related to sentiment peaks
plot.attributions | Plot prediction attributions at specified level
plot.sento_measures | Plot sentiment measures
plot.sento_modelIter | Plot iterative predictions versus realized values
predict.sento_model | Make predictions from a sento_model object
scale.sento_measures | Scaling and centering of sentiment measures
sentometrics | sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
sento_corpus | Create a sento_corpus object
sento_lexicons | Set up lexicons (and valence word list) for use in sentiment analysis
sento_measures | One-way road towards a sento_measures object
sento_model | Optimized and automated sentiment-based sparse regression
subset.sento_measures | Subset sentiment measures
usnews | Texts (not) relevant to the U.S. economy
weights_almon | Compute Almon polynomials
weights_beta | Compute Beta weighting curves
weights_exponential | Compute exponential weighting curves