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 |
fit.sentopicmodel | Estimate a topic model |
get_ECB_press_conferences | Download press conferences from the European Central Bank |
get_ECB_speeches | Download and pre-process speeches from the European Central... |
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 |
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