ECB_press_conferences   Corpus of press conferences from the European
                        Central Bank
ECB_press_conferences_tokens
                        Tokenized press conferences
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
PicaultRenault          Picault-Renault lexicon
PicaultRenault_data     Regression dataset based on Picault & Renault
                        (2017)
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
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 Bank
melt                    Replacement generic for 'data.table::melt()'
melt.sentopicmodel      Melt for sentopicmodels
mergeTopics             Merge topics into fewer themes
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
rJST                    Create a Reversed Joint Sentiment/Topic model
reset                   Re-initialize a 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
sentopics-package       Tools for joining sentiment and topic analysis
                        (sentopics)
sentopics_date          Internal date
sentopics_labels        Setting topic or sentiment labels
sentopics_sentiment     Internal sentiment
topWords                Extract the most representative words from
                        topics
