R: Semi-Supervised Algorithm for Document Scaling

# Semi-Supervised Algorithm for Document Scaling

## Documentation for package ‘LSX’ version 1.4.5

- DESCRIPTION file.
- Package NEWS.

## Help Pages

as.seedwords | Convert a list or a dictionary to seed words
as.textmodel_lss | Create a Latent Semantic Scaling model from various objects
bootstrap_lss | [experimental] Compute polarity scores with different hyper-parameters
char_context | Identify context words
coef.textmodel_lss | Extract model coefficients from a fitted textmodel_lss object
coefficients.textmodel_lss | Extract model coefficients from a fitted textmodel_lss object
data_dictionary_ideology | Seed words for analysis of left-right political ideology
data_dictionary_sentiment | Seed words for analysis of positive-negative sentiment
data_textmodel_lss_russianprotests | A fitted LSS model on street protest in Russia
optimize_lss | [experimental] Compute variance ratios with different hyper-parameters
predict.textmodel_lss | Prediction method for textmodel_lss
seedwords | Seed words for Latent Semantic Analysis
smooth_lss | Smooth predicted polarity scores
textmodel_lss | Fit a Latent Semantic Scaling model
textmodel_lss.dfm | Fit a Latent Semantic Scaling model
textmodel_lss.fcm | Fit a Latent Semantic Scaling model
textplot_simil | Plot similarity between seed words
textplot_terms | Plot polarity scores of words
textstat_context | Identify context words