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-package
|
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 |