Semi-Supervised Algorithm for Document Scaling
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Documentation for package ‘LSX’ version 1.4.5
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 |