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

## Documentation for package ‘sentometrics’ version 0.5.6

- DESCRIPTION file.

## 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 documents and time
attributions | Retrieve top-down model sentiment attributions
compute_sentiment | Compute document-level sentiment across features and lexicons
ctr_agg | Set up control for aggregation into sentiment measures
ctr_model | Set up control for sentiment-based sparse regression modelling
diff.sentomeasures | Differencing of sentiment measures
epu | Monthly 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
get_measures | Get the sentiment measures
list_lexicons | Built-in lexicons
list_valence_shifters | Built-in valence word lists
measures_delete | Delete sentiment measures
measures_fill | Add and fill missing dates
measures_global | Merge sentiment measures into multiple weighted global sentiment indices
measures_merge | Merge sentiment measures
measures_select | Select sentiment measures
measures_subset | Subset sentiment measures
nmeasures | Get number of 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.sentomeasures | Plot sentiment measures
plot.sentomodeliter | Plot iterative predictions versus realized values
predict.sentomodel | Make predictions from a sentomodel object
scale.sentomeasures | Scaling and centering of sentiment measures
sentiment_bind | Bind sentiment objects row-wise
sentometrics | sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
sento_corpus | Create a sentocorpus object
sento_lexicons | Set up lexicons (and valence word list) for use in sentiment analysis
sento_measures | One-way road towards a sentomeasures object
sento_model | Optimized and automated sentiment-based sparse regression
to_sentiment | Convert a sentiment table to a sentiment object
to_sentocorpus | Convert a quanteda corpus object into a sentocorpus object
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