An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

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Documentation for package ‘sentometrics’ version 0.5.6

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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