Function reference • SegmentR

Topic Modelling

Functions for finding latent topics in text.

make_DTMs(): Create a Document Term Matrix (DTM) from a data frame

fit_LDAs(): fit LDA topic models on Document Term Matrices

explore_LDAs(): Explore & Visualise LDA topic models

shiny_topics_explore(): Render a Shiny app to interactively explore topic models

Utility Functions

Functions which help the user join the topics to original data frame, classify them and rename them for plotting

topics_link(): Link topics and their probabilities back to the original data frame.

topics_classify(): Classify the topics in your linked data frame

topics_rename(): Rename the topics after classifying and linking

top_terms_rename(): Quickly rename the topics of the top_terms charts

Explore Functions

The funcitons called by explore_LDAs

bigrams_segmentr(): Bigram/ngram viz Function

coherence_segmentr(): Coherence for each topic

diff_terms_segmentr(): Diff Terms Function

exemplars_segmentr(): Example posts for each topic

probabilities_segmentr(): Topic Probabilities per post

top_terms_segmentr(): The Top Terms

Example datasets

Toy datasets for testing the functions.

sprinklr_export: Example Sprinklr Export