Man pages for sentopics
Tools for Joint Sentiment and Topic Analysis of Textual Data
| as.LDA | Conversions from other packages to LDA |
| as.tokens.dfm | Convert back a dfm to a tokens object |
| chainsDistances | Distances between topic models (chains) |
| chainsScores | Compute scores of topic models (chains) |
| coherence | Coherence of estimated topics |
| compute_PicaultRenault_scores | Compute scores using the Picault-Renault lexicon |
| ECB_press_conferences | Corpus of press conferences from the European Central Bank |
| ECB_press_conferences_tokens | Tokenized press conferences |
| get_ECB_press_conferences | Download press conferences from the European Central Bank |
| get_ECB_speeches | Download and pre-process speeches from the European Central... |
| grow | Estimate a topic model |
| JST | Create a Joint Sentiment/Topic model |
| LDA | Create a Latent Dirichlet Allocation model |
| LDAvis | Visualize a LDA model using 'LDAvis' |
| LoughranMcDonald | Loughran-McDonald lexicon |
| melt | Replacement generic for 'data.table::melt()' |
| melt.sentopicmodel | Melt for sentopicmodels |
| mergeTopics | Merge topics into fewer themes |
| PicaultRenault | Picault-Renault lexicon |
| PicaultRenault_data | Regression dataset based on Picault & Renault (2017) |
| plot.multiChains | Plot the distances between topic models (chains) |
| plot.sentopicmodel | Plot a topic model using Plotly |
| print.sentopicmodel | Print method for sentopics models |
| proportion_topics | Compute the topic or sentiment proportion time series |
| reexports | Objects exported from other packages |
| reset | Re-initialize a topic model |
| rJST | Create a Reversed Joint Sentiment/Topic model |
| sentiment_breakdown | Breakdown the sentiment into topical components |
| sentiment_series | Compute a sentiment time series |
| sentiment_topics | Compute time series of topical sentiments |
| sentopicmodel | Create a sentopic model |
| sentopics-conversions | Internal conversions between *sentopics* models. |
| sentopics_date | Internal date |
| sentopics_labels | Setting topic or sentiment labels |
| sentopics-package | Tools for joining sentiment and topic analysis (sentopics) |
| sentopics_sentiment | Internal sentiment |
| topWords | Extract the most representative words from topics |
